ACE’14 Workshop on “Designing Systems for Health and Entertainment: what are we missing?”
2014/11/11

Systems that aggregate health and entertainment goals are proliferating, but little is known about the way to design and evaluate these systems and how to manage the different (if nor opposite) needs of these two main areas. This workshop will promote the discussion of issues surrounding these areas, enabling a better understanding of the how’s and why’s of designing systems for health and entertainment, as well as the identification of new avenues of research in the field.
Therefore we invite designers, researchers and practitioners to participate in an exciting full-day workshop where they are invited to share their personal views and research on the intersection of technology, health and entertainment.

More information at http://designingsystemsforhealthandentertainment.wordpress.com/.

SMBM 2014
2014/10/06to2014/10/07

The 6th International Symposium on Semantic Mining in Biomedicine (SMBM)
6th-7th October, 2014 will be held at the University of Aveiro, Portugal.

SMBM aims to bring together researchers from text and data mining in biomedicine, medical, bio- and chemoinformatics, and researchers from biomedical ontology design and engineering. SMBM 2014 is the follow-up event to SMBM 2012 (University of Zürich, Switzerland) SMBM 2010 (EBI, U.K.), SMBM 2008 (University of Turku, Finland), SMBM 2006 (University of Jena, Germany), and SMBM 2005 (EBI, U.K.).

More information at http://www.smbm.org.

PhD Defense (Luis Ribeiro)
2014/05/09
14:30to17:30

Luis Ribeiro, “Platform for on-demand exchange of medical imaging communities”
Universidade de Aveiro, DETI/IEETA

PhD Defense (David Campos)
2014/02/28
10:00to13:00

David Campos, “Term expansion methodologies in biomedical information retrieval”
Universidade de Aveiro, DETI/IEETA

Sérgio Matos was awarded a FCT Investigator grant

The FCT Investigator Programme aims to create a talent base of scientific leaders, by providing 5-year funding for the most talented and promising researchers, across all scientific areas and nationalities.

For the 2013 call, Sérgio Matos, research assistant at IEETA, was awarded a FCT Investigator grant, for the 2014-2018 period.

Dna-at-glance

dnaatglance_topDNAatGlance is a program for the detection of large-scale genomic regularities by visual inspection. Several discovery strategies are possible, including the standalone analysis of single sequences, the comparative analysis of sequences from individuals from the same species, and the comparative analysis of sequences from different organisms. The software was designed and implemented at IEETA, a research unit of the University of Aveiro, and is available for non-commercial use.

Citation

Armando J. Pinho, Sara P. Garcia, Diogo Pratas, Paulo J. S. G. Ferreira (2013) DNA Sequences at a Glance. PLoS ONE 8(11): e79922.
DOI: dx.doi.org/10.1371/journal.pone.0079922.

Download

For convenience, we provide a sequence (here in gzip)(here in zip) and the corresponding information profile in WIG format (here in gzip) (here in zip) that can be uploaded to the UCSC Genome Browser as a custom track.

MFCompress

MFCompress: a compression tool for FASTA and multi-FASTA dataMFCompress

About

MFCompress is a compression tool for FASTA and multi-FASTA files. In comparison to gzip and applied to multi-FASTA files, MFCompress can provide additional average compression gains of almost 50%, i.e., it potentially doubles the available storage, although at the cost of some more computation time. On highly redundant data sets, and in comparison with gzip, 8-fold size reductions have been obtained. MFCompress was designed and implemented at IEETA, a research unit of the University of Aveiro, and is available for non-commercial use. For other uses, please send an email to ap@ua.pt.

Citation

Armando J. Pinho, and Diogo Pratas. “MFCompress: a compression tool for FASTA and multi-FASTA data.” Bioinformatics 30.1 (2014): 117-118.
DOI: dx.doi.org/10.1093/bioinformatics/btt594.

Download
egas

What?

Egas is a web-based platform for biomedical text mining and collaborative curation. The web tool allows users to annotate texts with concept occurrences as well as with relations between concepts. Annotations can be performed manually or based on the results of automated concept identification and relation extraction tools. These automatic annotations may have been previously added to the documents, using one of the accepted input formats, or may be added during the annotation process, by calling a document annotation service. Users can inspect, correct or remove automatic text mining results, manually add new annotations, and export the results to standard formats.

How?

Text-processing and fetching modules, such as the concept and relation annotation services, were implemented in Java, and the web interface was developed using HTML5, CSS3, and JavaScript, in order to allow fast processing of large documents and support mobile devices. The resulting information is stored in a relational database. Finally, all database operations are performed using secured RESTful web-services, allowing easy integration with mobile devices, such as smartphones and tablets.

Cloud Thinking

Funding entity: QREN MaisCentro
Period: Feb.2013 – Dec.2014

The projects’ ambition is the creation of a new set of solutions based in novel ICT technologies, developing a concept that encompasses the synergistic usage of cloud computing, with large database access and information retrieval, associated with advanced methods for reasoning and data mining (and with the basic scalable algorithms to support the dimensions of the data sets targeted).

web site

NeuroPath – New Strategies Applied to Neuropathological Disorders

Funding entity: QREN MaisCentro
Period: Feb.2013 – Jun.2015

Neurodegenerative disorders are a major health concern worldwide, Portugal being no exception. With this project the University of Aveiro proposes extend existing research in the field of neurodegenerative diseases through the creation of a consortium of 5 research units from UA (CBC, QOPNA, I3N, IEETA, CICECO). The projects main goal is to offer novel therapeutic strategies to tackle the complex array of existing neuropathologies. By building a multidisciplinary research team that combines experts in molecular neuropathologies, proteomics, metabolomics, bioinformatics, neuronal networks, organic synthesis and drug design from the UA we will be able to attack the problem on many fronts. Upon successful completion of this project, new therapeutic approaches will have been developed which will contribute to the improvement of life quality for neurodegenerative patients, having a high society impact considering the 10 million new patients reported every year.

Best Poster award at BioLINK SIG 2013

The price was awarded at BioLINK SIG 2013 for the work “Neji: a tool for heterogeneous biomedical concept identification”.

BioLINK SIG 2013: Roles for text mining in biomedical knowledge discovery and translational medicine
The Annual Meeting of the ISMB BioLINK Special Interest Group
In Association with ISMB/ECCB 2013, Berlin, Germany
July 20, 2013

iOS Development Seminar (Rui Pedro Lopes)
2013/07/29
10:00to18:00

A 6-hour iOS Development Seminar will be held by Rui Pedro Lopes, Professor at Polytechnic Institute of Brangança, on the 29th July 2013, at Department of Electronics, Telecommunications and Informatics (DETI), Aveiro.

This Seminar will cover the following main topics: Objective-C, Storyboards, Core Data, Master-Detail User Interface

Universidade de Aveiro, DETI, Room 102, 10h

Variobox

VarioboxExploring Human Genetic Variations

About

Variobox is a desktop tool for the annotation, analysis and comparison of human genes. Variant annotation data are obtained from WAVe, protein metadata annotations are gathered from PDB and UniProt, and sequence metadata is obtained from Locus Reference Genomic (LRG) and RefSeq databases. By using an advanced sequence visualization interface, Variobox provides an agile navigation through the various genetic regions. Researched genes are compared to the sequences retrieved from LRG and RefSeq, automatically finding and annotating new potential mutations. These features and data, ranging from patient sequences to HGVS-valid variant description up to pathogenicity evaluation, are combined in an intuitive interface to explore genes and mutations.

Citing

To cite this tool use the following publication:

Variobox: Automatic Detection and Annotation of Human Genetic Variants. Paulo Gaspar, Pedro Lopes, Jorge Oliveira, Rosário Santos, Raymond Dalgleish, José Luís Oliveira. Human Mutation, 2014

Download

VarioBox is available for all the main operating systems (Windows [XP, 7, 8]; Linux; MacOS) that support Java. The current version of the software is 1.4.4. Click the link bellow to download:

Download Variobox

To run, first unpack all the files to any folder. Then, if you’re on Windows, double click the Variobox file inside the folder. On Mac or Linux, start a terminal, change the directory to the created folder, and run java -jar variobox.jar

Tutorial
Step 1 The initial layout

main_windowThis is the initial VarioBox workspace that shows up when you open the application. At the bottom of the workspace you can find a separator, “Home”, created automatically. Here will be as many separators as searches performed, each one identified by the searched HGNC code. At the centre you can see the logo and a panel, where searches for reference genes can be performed, using a valid HGNC symbol. To work with Variobox, a reference gene is always the starting point. After obtaining the reference, a sequence can be loaded to the application to be aligned with the sequence, and analysed.

Step 2 Making a quick search

By default there are two genes bellow the search box: Collagen, type I, alpha 1 (COL1A1), and Myotubularin 1 (MTM1). Click on COL1A1 or type it at the search box and hit search. A progress bar will show up indicating the progress of the loading process. A new tab (with the name of the searched HGNC code), like the one below, will show up once the reference gene is automatically retrieved from the web servers:

main_window2

The right zone is formed by two distinct panels:

  • The top one, titled Protein Viewer is where the 3D protein conformation of the selected gene is shown, if available, using JMol.
  • The bottom one, titled Information Panel, which will display additional information on selected items, such as mutations and exons.

On the top of the window there is a large genomic viewer with a movable and resizable window that allows specifying a region to be explored in the centre zone. This viewer distinguishes exons (blue) and introns (purple), and allows quickly jumping through the gene. The centre zone is populated with gene data and information, in three distinct panels, described below:

  • Gene panel

In this panel you can see the codon sequence and the decoded polypeptide sequence, labelled Reference Sequence and Translated Sequence respectively, and also the Known Mutations for the gene, as retrieved from WAVe. A zoomed genomic viewer is also displayed to further facilitate the exploration of the gene.

genepanel

Mutations are identified by different colours, and shown next to the corresponding nucleotides. Additional information about a mutation can be obtain by clicking on the mutation. The Information Panel (right side of the workspace) will display details regarding the selected mutation’s position, source, type, annotation, etc.

information_panel

  • Navigation panel
The navigation panel is a simple feature that allows the easy exploration of the gene through mutations and exons. Clicking on the next or previous buttons will centre the sequence in the appropriate item (a mutation or exon):
nav_panel

The Navigation Panel also permits filtering what mutation types are to be shown in the Gene Panel. For instance, if you only check Substitutions, all mutations besides SNPs will be hidden.

  • Gene Details panel

This panel shows you a quick information about the gene that you are analysing. The current information supported is the following:

  • Number of mutations: displays the total number of mutations found in the reference gene. No information will be displayed if no mutations are known;
  • Number of exons: total number of exons found in the gene;
  • Sequence size: total size of the reference sequence;
  • Date of creation: the date and time when this gene was created;
  • Loaded files: the files that were selected by the user to be aligned with the reference sequence.

Gene details

Step 3 Loading mutated sequences

To load a gene sequence and align it with the reference gene, click the menu Genes  Load gene file. Alternatively, go to the menu File  Load gene fileYou will be prompted with a new window to select the file you want to load. For the current version we support the file types:

  • DNA Sequence Chromatogram File: .scf ; .abi extension
  • DNA Electropherogram File: .ab1 extension
  • FASTA files: .fasta ; .fa extension

After selecting the file (or files, if you choose the forward-reverse format), click Load selected file and VarioBox will read them. Once the file is correctly loaded, an alignment with the reference gene is automatically performed. This alignment will also display found mutations, as compared to the reference gene. The analysis of the loaded sequence is described in the next step.

Step 4 Analysing mutated sequences and saving results

After the files are loaded, the Gene Panel will be updated with the mutated sequence as well as the calculated mutations, as depicted in the following figure:

genepanel2

The loaded sequence will also be coloured according to its chromatogram confidence (if there is one), ranging from green (high confidence) to red (no confidence). This will allow easily understanding the validity of calculated mutations. Also note that the mutations are automatically annotated using the standard notation, and its annotation is displayed when clicking on a mutation. To save the sequences, mutations, alignment and other information, the gene should be assigned to a patient. To do so, go to the menu Genes → Save to patient and select a patient from the list of patients that will be presented.

Step 5 Final Features

If you want to register a new patient in VarioBox, make the following steps: Go to Patients → New patient and fill the Patient Details panel (shown bellow) with all the required information(note that only one field is mandatory). After that just click Save patient and a new record will be created.

Patient details

To load a saved project, go to Patients → Open patient and select the patient you previously saved. This will create a new tab with all the patient information: patient personal information as well as the genes from that patient. Those genes can be open just by selecting them and clicking Open selected.
This action will open many tabs as many genes you have selected and will re-create all the gene panels you had in the workspace previously.

Closing tabs is as simple as going to Patients → Close patient or Genes → Close current gene project depending of the tab type you have open.

becas

BeCAS Logo
Biomedical Concept Annotation Tool, API and Widget

About

becas is a web application, API and widget for biomedical concept identification. It helps researchers, healthcare professionals and developers in the identification of over 1,200,000 biomedical concepts in text and PubMed abstracts.

becas provides annotations for isolated, nested and intersected entities. It identifies concepts from multiple semantic groups, providing preferred names and enriching them with references to public knowledge resources. You can choose the types of entities you want to identify and highlight or mute specific entities in real-time.

To facilitate annotation of PubMed abstracts, becas automatically fetches publications from NCBI servers and renders them with identified concepts highlighted.

Using becas

You can access the becas web annotation tool here and learn to use it in its help page. Explore the Web API in the API docs and discover how easy it is to integrate the becas widget in the widget docs.

You can read more about becas in the about page and we would love to hear your feedback!

Diseasecard

Diseasecard is a public web portal that integrates real-time information from distributed and heterogeneous medical and genomic databases, presenting it in a familiar visual paradigm.

[website]

Bioinformatics is playing a key role on molecular biology advances, not only by enabling new methods of research, but also managing the huge amounts of relevant information and make it available world-wide.

State of the art methods on bioinformatics include the use of public databases to publish the scientific breakthroughs. These databases provide valuable knowledge for the medical practice. But, given their specificity and heterogeneity, we cannot expect the medical practitioners to include their use in routine investigations. To obtain a real benefic from them, the clinician needs integrated views over the vast amount of knowledge sources, enabling a seamless querying and navigation.

Goals

Main goals behind the conception of DiseaseCard:

  • Provide the user with an integrated view of the information available in the internet for a specific disease, from the phenotype to the genotype.
  • Use rare diseases as the main target due to the high association between phenotype and genotype.
  • Do not replicate information that already exists in public or private databases. The system is based in an information model that allows accessing and sharing these data;
  • Be supported in a navigation protocol that allows guiding users in the process of retrieving information from the Internet.
 DiseaseCard

DiseaseCard

Results

Diseasecard can provide the answers to several questions that are relevant in the genetic diseases diagnostic, treatment and accomplishment, such as:

  • What are the main features of the disease?
  • Are there any drugs for the disease?
  • Are there any gene therapies for the disease?
  • What laboratories perform genetic tests for the disease?
  • What genes cause the disease?
  • On which chromosomes are these genes located?
  • What mutations have been found in these genes?
  • What names are used to refer to these genes?
  • What are the proteins coded by these genes?
  • What are the functions of the gene product?
  • What is the 3D structure for these proteins?
  • What are the enzymes associated to these proteins?

Publications

  • G. Dias, J. L. Oliveira, F. Vicente, and F. Martín-Sanchez, “Integrating Medical and Genomic Data: a Sucessful Example for Rare Diseases”, in The XX International Congress of the European Federation for Medical Informatics (MIE’2006), Maastricht, Netherlands, 2006.
  • G. Dias, J. L. Oliveira, F. Vicente, and F. Martin-Sanchez, “Integration of Genetic and Medical Information Through a Web Crawler System”, in Biological and Medical Data Analysis (ISBMDA’ 2005), Lecture Notes in Computer Science – Volume 3745, Aveiro, Portugal, 2005.
EU-ADR Web Platform
eu-adr logo

The EU-ADR Web Platform helps experts in the study of adverse drug reactions (ADRs) through the use of computational services and scientific workflows, provided by several European partners. The system assists in the earlier detection of adverse drug reactions, improving drug safety and contributing to public health benefit. You can access the EU-ADR Web Platform here

View the manuscript

EU-ADR Project

The overall objective of this project was the design, development and validation of a computerized system that exploits data from electronic healthcare records and biomedical databases for the early detection of adverse drug reactions. Visit the project page.

An eHealth Successful Project

On Multicriteria Pairwise Sequence Alignment: Algorithms and Applications
2013/01/23
14:30to15:30

Talk from Luís Paquete, Anf. IEETA

The multiobjective formulation of the pairwise sequence alignment problem is introduced, where a vector score function takes into account the substitution score and indels or gaps separately. Two solution methods are introduced: a multiobjective dynamic programming that extends classical algorithms for this problem and an epsilon-constraint algorithm that solves a series of constrained sequence alignment problems. A state pruning technique based on the concept of bound sets is also presented. Finally, its application to phylogenetic tree construction is
discussed.

Universidade de Aveiro, Anf. IEETA, 14h30

EMIF – European Medical Information Framework

Funding entity: IMI-JU
Period:
2013-2018

In recent years, the development and use of Electronic Healthcare Records (EHRs) throughout Europe has grown exponentially resulting in large volumes of clinical data. At the same time, large collections of disease‐specific data are recorded – in local, regional and/or national settings. Researchers also follow specific cohorts over time, and focus on specific types of data such as imaging or genetic data. Other researchers are building biobanks that aim to combine clinical data with genetic data. As a result, individual patients can contribute to multiple, often separate, data sources.
This project combines the topic of generating a common patient health Information Framework (IF) with addressing the two Research Topics (RT’s) Obesity and its metabolic complications and Markers for the development of Alzheimer’s disease (AD) and other dementias.

web site

RD-CONNECT – An integrated platform connecting registries, biobanks and clinical bioinformatics for rare disease research

Funding entity: FP7-HEALTH-2012-INNOVATION-1
Period:
2012-2018

Despite examples of excellent practice, rare disease (RD) research is still mainly fragmented by data and disease types. Individual efforts have little interoperability and almost no systematic connection between detailed clinical and genetic information, biomaterial availability or research/trial datasets. By developing robust mechanisms and standards for linking and exploiting these data, RD-Connect will develop a critical mass for harmonisation and provide a strong impetus for a global “trial-ready” infrastructure ready to support the IRDiRC goals for diagnostics and therapies for RD patients.

web site

Neji

Flexible, easy and powerfull framework for faster biomedical concept recognition.
Download Learn more

What?

Neji is an innovative framework for biomedical concept recognition. It is open source and built around four key characteristics: modularity, scalability, speed, and usability. It integrates modules of various state-of-the-art methods for biomedical natural language processing (e.g., sentence splitting, tokenization, lemmatization, part-of-speech tagging, chunking and dependency parsing) and concept recognition (e.g., dictionaries and machine learning). The most popular input and output formats, such as Pubmed XML, IeXML, CoNLL and A1, are also supported. Additionally, the recognized concepts are stored in an innovative concept tree, supporting nested and intersected concepts with multiples identifiers. Such structure provides enriched concept information and gives users the power to decide the best behavior for their specific goals, using the included methods for handling and processing the tree.

Why?

Concept recognition is an essential task in biomedical information extraction, presenting several complex and unsolved challenges. The development of such solutions is typically performed in an ad-hoc manner or using general information extraction frameworks, which are not optimized for the biomedical domain and normally require the integration of complex external libraries and/or the development of custom tools. Thus, Neji fills the gap between general frameworks (e.g., UIMA and GATE) and more specialized tools (e.g., NER and normalization), streamlining and facilitating complex biomedical concept recognition.

How?

On top of the built-in functionalities, developers and researchers can implement new processing modules or pipelines, or use the provided command-line interface tool to build their own solutions, applying the most appropriate techniques to identify names of various biomedical entities. Neji was built thinking on different development configurations and environments: a) as the core framework to support all developed tasks; b) as an API to integrate in your favorite development framework; and c) as a concept recognizer, storing the results in an external resource, and then using your favorite framework for subsequent tasks.

 

Systems Biology seminars series start on the 28th of September

Universidade de Aveiro, Anf. Ambiente, 14h

PhD Defense (Pedro Lopes)
2012/10/01
14:30to17:30

Pedro Lopes, “Service Composition in Biomedical Applications”
Universidade de Aveiro, DETI/IEETA

Talk (Kim Sneppen)
2012/09/28
14:00to16:00

Dr. Kim Sneppen from the Niels Bohr Institute, Copenhagen-DK, will give the give the inaugural Lecture of our Systems Biology seminars series entitled Simplified Models of Biological Networks, on the 28th of September.

Universidade de Aveiro, Anf. Ambiente, 14h

mRNA Optimiser

Redesign mRNA sequences to optimise the secondary structure

About

The mRNA optimiser is a tool that redesigns a gene messenger RNA to optimise its secondary structure, without affecting the polypeptide sequence. The tool can either maximize or minimize the molecule minimum free energy (MFE), thus resulting in decreased or increased secondary structure strength.

The optimisation is achieved by using an heuristic to look for synonymous gene sequences, and select the ones with the best secondary structure. Evaluations of the secondary structure are made using a correlated stem-loop prediction algorithm that examines the nucleotide sequence for simple stem-loops. This algorithm is fine-tuned to have its results  highly correlated with the MFE evaluations of RNAfold.

Our results indicate that an average of over 40% increase in MFE can be obtained with this method. Also, since there is a tendency to reduce the GC percentage of nucleotide sequences when optimising, the developed tool includes an option to maintain the GC content of the wildtype gene.

Citing

 

 
P. Gaspar, G. Moura, M. A. S. Santos, and J. L. Oliveira
mRNA secondary structure optimization using a correlated stem–loop prediction
Nucleic Acids Research, Jan 2013, doi: 10.1093/nar/gks1473

 

Download

Select your operating system:

      

Current version is 1.0.

Usage

The mRNA optimiser is a command line tool (a graphical interface will be available soon). To use it you need to open a terminal window, change to the directory where mRNAOptimiser is, and run it:

1. Open a terminal window

  • In Windows, go to the Start menu, click Run, write cmd, and click Ok.
  • In Mac, write terminal in spotlight and hit enter.

2. Change the directory

  • In Windows, Mac and Linux, write cd in the terminal followed by the directory where you placed the tool.

3. Run the mRNA optimiser

  • In Windows, write mRNAOptimizer.exe and hit enter. Usage indications will show up in the terminal.
  • In Mac and Linux, write java -jar mRNAOptimizer.jar and hit enter. Usage indications will show up in the terminal.

You may choose to supply your mRNA sequence by writing it into the terminal or referring an input file, with the -f input_sequence option. The tool only changes the coding region of the mRNA, therefore you must indicate where the start codon begins (-b index, to indicate the index of the first nucleotide of the start codon) and where the stop codon ends (-e index, to indicate the index of the last nucleotide of the stop codon). The default coding zone is the entire sequence.

To redirect the output results to a file, use the -o output_file option. To choose whether the tool should maximize or minimize the MFE, use the -d type option (default is maximize). You may limit the algorithm in both time and number of iterations by using the options -t max_time and -i max_iterations. Also, the tool will use the standard genetic code by default, but you can select other genetic coding tables using the -c coding_table option.

To maintain the original mRNA percentage of guanine and citosine (GC content) unaltered after optimisation, use the -g option. There is also a quiet mode, where nothing is output except for the resulting sequence, using the -q option.

Any questions and suggestions are welcome :)

OralCard

What is OralCard?

OralCard is an online bioinformatic tool that comprises results from manually curated articles reflecting the oral molecular ecosystem (OralPhysiOme), by merging the experimental information available from the oral proteome both of human (OralOme) and microbial origin (MicroOralOme). OralCard is a key resource for understanding the molecular foundations implicated in biology and disease mechanisms of the oral cavity.

How does it work?

OralCard integrates information about more than 3500 proteins and searching can be performed in three distinct views: (1) by protein names or respective UniProt codes, (2) by disease name, OMIM code or MeSH term, (3) and by organism.

PhD Defense (Nuno Rosa)
2012/05/30
14:30to17:30

Nuno Rosa, “From the Salivar Proteome to Oralome”
Universidade Católica Portuguesa, Viseu

International School on SWAT4LS 2012 (May 2nd – 5th, Aveiro)
2012/05/02to2012/05/05

International School on Semantic Web Applications and Technologies for the Life Sciences 2012
May 2nd – 5th, 2012
Located at the University of Aveiro,
Aveiro, Portugal

More information online at http://www.swat4ls.org/schools/aveiro2012/

Talk (Helena Deus)
2012/04/30
15:00to16:00

Helena Deus, “Linked Data and Semantic Web Technologies for improving discovery in the Life Sciences”

We live in a world of data. This is also true for the Life Sciences, where the introduction of omics technologies such as genome sequencing has led to the industrialization of data production beyond a craft-based cottage industry and into a deluge of biological information. Nevertheless, the apparently simple task of collecting and keeping pace with the latest information about a gene of interest is still thwarted by the need for biological researchers to become experts at database-surfing and literature mining.

Linked Data is a set of principles devised for creating a Web of Data where a new generation of Web applications can discover and link relevant pieces of information based on its properties rather than its location in a database. Linked data is also at the root of a movement towards building a knowledge continuum in the Life Sciences and by doing so, has the potential to be a foundation for a platform that will support 21st century Biology.

In this talk, I will present some of the scenarios where Linked Data has been successfully applied in accelerating scientific discovery and translation of Life Sciences knowledge into Health Care and what challenges are still to be addressed.

Helena Deus Bio at http://lenadeus.info

Best PhD work in the Fraunhofer Portugal Challenge 2011

III Workshop Ibero-NBIC – 2011
2011/10/10to2011/10/11

III WORKSHOP DE RED IBEROAMERICANA DE TECNOLOGÍAS CONVERGENTES NBIC EN SALUD (IBERO-NBIC) – CYTED Program

Hotel Moliceiro, Aveiro, Portugal
October 10-11, 2011

Day 1: Monday, 10

9h00 – 9h30: Opening and Welcome
Boas Vindas
José Luís Oliveira, DETI/IEETA, Universidade de Aveiro, Portugal
Acto de apertura del III Workshop Internacional Redes Ibero-NBIC y NanoRoadmap
Alejandro Pazos & Julián Dorado, Universidade da Coruña, España

9h30 – 11h15:
Vacunología inversa aplicada en malaria
Raúl Isea, IDEA, Fundación de Estudios Avanzados, Venezuela
Bioinformatics, research and applications
Sergio Guíñez Molinos, UCBSM, Universidad de Talca, Chile
Tecnologías NBIC y Nanotoxicidad: Gestión del conocimiento asociado al uso de nanopartículas en medicina
Diana de la Iglesia, GIB, Universidad Politécnica de Madrid, España
Tecnologías de la Información y el Conocimiento en Salud. Un Sistema Basado en Ontologías para el Apoyo a la Toma de Decisión en UCIs
Ana Freire, Universidade de Coruña, España

11h15 – 11h30: Coffee Break

11h30 – 13h00:
Integration of heterogeneous biomedical names taggers
David Campos, DETI/IEETA, Universidade de Aveiro, Portugal
Collecting and Enriching Human Variome Datasets
Pedro Lopes, DETI/IEETA, Universidade de Aveiro, Portugal
Doctoral Program in Nanosciences and Nanotechnology of the University of Aveiro
Tito Trindade, DQ, Universidade de Aveiro, Portugal

13h00 – 14h30: Lunch

14h30 – 16h00:
Integración de la información molecular en un Sistema de Informacion en Salud
Segunda etapa: estándares y control de calidad.
Carlos Otero, HIBA, Buenos Aires, Argentina
Connecting different levels of biological information. From atoms to people
Guillermo López, ISCIII – Instituto de Salud Carlos II, Madrid, España
Posibles aportes de una empresa de Educación Médica Continua a una red de investigación en Salud
Antonio López, EVIMED, Uruguay

16h00 – 16h30: Coffee Break

16h30 – 18h00:
Internal Meeting / Reunión Interna de la Red

Day 2: Tuesday, 11

Visit to Instituto Ibérico de Nanotecnologia (Braga)

Gimli
Annotation of biomedical entity names
the best open-source solution
Open Source
  • Use, change and distribute
  • Social development
High Performance*
  • BioCreative: 87,54%
  • JNLPBA: 73,05%
High-end Techniques
  • Linguistic dependency parsing
  • Model combination
Flexible and Scalable
  • Extensible architecture
  • Fast annotation
Easy to Use
  • Automated scripts
  • Java library
License
  • Creative Commons License
  • Non-commercial use
* Overall F-measure results achieved using the evaluation methods of the respective challenges.

About

Goal:
Gimli is a machine learning-based solution for biomedical Named Entity Recognition (NER), which goal is to automatically extract names of biomedical entities from scientific text documents. Currently, Gimli supports the recognition of gene/protein, DNA, RNA, cell line and cell type names.
In summary, Gimli receives raw text as input, and provides text with specific annotations as output.
Methods:
  • Machine Learning: Conditional Random Fields (CRFs);
  • Features: orthographic, morphological, linguistic parsing and conjunctions;
  • Combination: combination of models with different orders and parsing directions;
  • Post-processing: parentheses correction and abbreviation resolution.
Publication(s):

Download

Tool:
Get the latest official release of Gimli.
Source code:
Get a copy of the project using the following git command:
git clone git://github.com/davidcampos/gimli.git

Documentation

Full documentation:
Complete information about alternative downloads, installation and usage.
API Javadoc:
Detailed classes, methods and propreties description.

Join us

We have several ideas to make Gimli the most complete and efficient tool for biomedical information extraction. You are welcome to join us and contribute to the development of new and improved features. Please contact us:
david.campos(a)ua.pt

Team

Totum
 
Gold Standard Corpora
Documentation
Library and Tool will be available soon!

Problem

The recognition of named entities is a crucial initial task of biomedical text mining. A number of NER solutions have been proposed in recent years, taking advantage of different resources and/or techniques. Currently, the best results are achieved by combining the output of different systems. However, little effort has been spent in such harmonisation solutions, being specific to a corpus and/or non-knowledge based.

Features

Conceptual
  • Knowledge-based harmonisation
  • Correct, remove and create annotations
  • Support several biomedical domains and organisms
  • On-demand harmonisation
  • Support both NER and normalisation systems
Technical
  • Automated scripts for simple usage
  • Java library for advanced users
  • Input and Output in IeXML format

Method

Totum is a innovative harmonisation solution based on Conditional Random Fields, which were trained on several manually curated corpora. Thus, we avoid the single corpus dependency, supporting several biomedical domains and organisms. In the end, Totum harmonises gene/protein annotations provided by several heterogeneous NER solutions, following the gold standard requirements.

 

Results

Considering a corpus that contains the test parts of the four corpora, the experiments show that Totum improves the F-measure of state-of-the-art tagging solutions by up to 10% in exact alignment and 22% in nested alignment. Finally, Totum achieves an F-measure of 70% (exact matching) and 82% (nested matching) against the same corpus.

Used tools

  • MALLET: framework for statistical natural language processing, providing a Conditional Random Fields implementation;
  • Apache OpenNLP: tokenisation and respective model;
  • IeXML: annotation guidelines and associated library;
  • monq.jfa: fast and flexible text filtering with regular expressions.

Publication(s)

  • David Campos, Sérgio Matos, Ian Lewin, José Luís Oliveira, Dietrich Rebholz-Schuhmann. Harmonisation of gene/protein annotations: towards a gold standard MEDLINE. Bioinformatics, vol. 28, no. 9, p. 1253-1261, March 2012. doi:10.1093/bioinformatics/bts125

Team

Partners
 
  

Members
  • David Campos, david.campos(at)ua.pt
  • Sérgio Matos, aleixomatos(at)ua.pt
  • Ian Lewin, lewin(at)ebi.ac.uk
  • José Luís Oliveira, jlo(at)ua.pt
  • Dietrich Rebholz-Schuhmann, rebholz(at)ebi.ac.uk
COEUS

COEUS main web server is down for maintenance. It will be online again on February 27th, 2013. Thank you for your patience.

Ipsa scientia potestas est. Knowledge itself is power.
Streamlined back-end framework for rapid semantic web application development.

Get it Here

GitHub project

integrate

Integration

Create custom warehouses, integrating distributed and heterogeneous data.
Integrate CSV, SQL, XML or SPARQL resources with advanced Extract-Transform-Load warehousing features.
cloud

Cloud-based

Deploy your knowledgebase in the cloud, using any available host.
Your content – available any time, any where. And with full create, read, update, and delete support.
semantic

Semantics

Use Semantic Web & LinkedData technologies in all application layers.
Enable reasoning and inference over connected knowledge.
Access data through with LinkedData interfaces and deliver a custom SPARQL endpoint.
rapid

Rapid Dev Time

Reduce development time. Get new applications up and running much faster using the latest rapid application development strategies.
COEUS is the back-end framework, the client-side is language-agnostic: PHP, Ruby, JavaScript, C#… COEUS’ API works everywhere.
network

Interoperability

Use COEUS advanced API to connect multiple nodes together and with any other software.
Create your own knowledge network using SPARQL Federation enabling data-sharing amongst a scalable number of peers
distribute

Ecosystem

Launch your custom application ecosystem. Distribute your data to any platform or device.
Reach more users and create new semantic cloud-based software platforms.

XGB 2011 Best poster award
WAVe

The Human Variome relates to genomic mutations and their effects on particular phenotypes. This critical life sciences research field has grown greatly in recent years, mostly due to the appearance of projects such as the Human Variome Project or the European GEN2PHEN Project. Nonetheless, locus-specific mutation databases and included variants are far from being standardized and widely used in the research community workflow. With WAVe, we offer centralized and transparent access to these databases, combined with the integration of found variants in a single system that is enriched with the most relevant gene-related information in a user-friendly web-based workspace.
http://bioinformatics.ua.pt/WAVe

Features

WAVe provides a comprehensive set of features that will improve bioligists’ workflow when researching in the genomic variation field.

Search

Searching for genes only requires that users start typing the gene HGNC-approved symbol in any of the available search boxes. This event will trigger the automatic suggestion system that will offer various solutions based on users’ input. Following one of the suggestions leads directly to the gene view interface. When a suggestion is not accepted and there is more than one match, WAVe will display the gene browse interface, containing only the results matching the provided query.

Browse

Querying for * lists all genes as well as available LSDBs and variants for each gene. In this gene browse scenario, searches for a particular gene can be performed, in real time, by typing in the table search box. By clicking in one of the genes, users are sent to the gene view interface.

View

The gene view interface is the main WAVe workspace. The layout is divided in two main areas: the sidebar and the content zone. The sidebar displays minimal gene information on top – gene HGNC symbol, name and locus – and the navigation tree, which is WAVe’s user interface key element, at the bottom. The navigation tree is organized in nodes, each referring to a distinct data type: each node leaf links directly to a page containing information regarding a specific topic. Pages linked in each leaf appear in the content zone. This enables loading external applications without leaving WAVe’s interface and, thus, without losing focus with ongoing research.

API

Programmatic access to data is also available. The gene tree is available as an easily-parsable feed. Feeds are obtained by appending the atom tag (or other format: rss, json) to the end of the gene view address. For instance, BRCA2 Atom feed is available at http://bioinformatics.ua.pt/WAVe/gene/BRCA2/atom .
WAVe also provides an RSS API for variant access. With this, you have programmable access to all available variants for a given gene. For instance, BRCA2 variants (from multiple LSDBs) are at http://bioinformatics.ua.pt/wave/variant/BRCA2/atom. In addition to the variant description, WAve points to the original LSDB containing the variant.
This WAVe makes WAVe the only platform capable of providing aggregated variant listings through both visual and programmable access.

Feedback

We highly appreciate any feedback you can provide regarding WAVe and the genomic variation field. To do this, you can simply send an e-mail to pedrolopes@ua.pt. Thank you.

Talk (Daniel Sobral)
2011/05/10
11:00to12:00

Daniel Sobral, “Ensembl Regulation”

Ensembl is a world reference for vertebrate genome annotation, providing high quality annotation for more than 50 species. Particularly challenging is the annotation of non-coding functional regions of the genome. Ensembl Regulation aims at making Ensembl
a reference for the annotation of genomic features with a potential role in the transcriptional regulation of gene expression. Combining publicly available data from large projects like ENCODE and The Epigenomics Roadmap, we group overlapping areas of open chromatin and transcription factor binding to build a “best-guess” set of regulatory features, in a cell-aware manner. Finally, we also include histone-modification and polymerase data to generate cell-specific classifications for the regulatory regions. Taking advantage of the role of the EBI as part of the ENCODE data analysis group, we aim at bringing Ensembl to the forefront of the annotation of the regulatory genome.

smash
evolution puzzle
About
Smash is a completely alignment-free method/tool to find and visualize genomic rearrangements. The detection is based on conditional exclusive compression, namely using a FCM (Markov model), of high context order (typically 20). For visualization, Smash outputs a SVG image, with an ideogram output architecture, where the patterns are represented with several HSV values (only value varies). The method can perform both in small- and large-scale. Nevertheless is more directed to large-scale since that the main aim of the research is to know where the large-scale [chromosomal by chromosome] of several primates was equal/different, having at a glance a map of the entire genomes. Therefore the method aims to solve evolutionary species Rubik’s cube. The following image, illustrating the information maps between human and chimpanzee for the several chromosomes, depicts such an example study:

evolution puzzle
Download
Citation
Diogo Pratas, Raquel M. Silva, Armando J. Pinho, Paulo J. S. G. Ferreira. An alignment-free method to find and visualize genomic rearrangements. Mag-to-appear, 2014.
DOI: doi-to-appear
PhD Defense (Daniel Polónia)
2011/05/09
10:30to13:30

Daniel Polónia, “An electronic market for teleradiology services”

PhD Defense (José Paulo Lousado)
2011/04/11
10:00to13:00

José Paulo Lousado, “Pattern analysis on DNA primary structure”

EU-ADR – Early Detection of Adverse Drug Events by Integrative Mining of Clinical Records and Biomedical Knowledge

Funding entity: FP7-ICT (STREP)
Period:
2008-2012

The overall objective of this project is the design, development and validation of a computerized system that exploits data from electronic healthcare records and biomedical databases for the early detection of adverse drug reactions.

An eHealth Successful Project

eu-adr logo

GeNS

Genomic Name Server

The integration of heterogeneous data sources has been a fundamental problem in database research over the last two decades. The goal is to achieve better methods to combine data residing at different sources, under different schemas and with different formats in order to provide the user with a unified view of the data. Although simple in principle, due to several constrains, this is a very challenging task where both the academic and the commercial communities have been working and proposing several solutions that span a wide range of fields. However, the limitations found on most solutions reflect the difficulty to obtain a simple but comprehensive schema able to accommodate the heterogeneity of the biological domain while maintaining an acceptable level of performance: GeNS is our proposal towards solving this issue.

Installing and using GeNS

The Genomic Name Server can be either downloaded and installed on a local computer or accessed by Web Services. Please keep in mind that GeNS currently requires over 10 GB of disk space and this figure is likely to increase in the near future. Therefore, if disk space is a serious restriction you should consider using the available Web Services. We are currently using
Microsoft SQL Server 2008 but GeNS can be set up in any other DBMS.

a) Setting up a local instance of GeNS

  • Download either the full backup of the database (here) or a dump of all the tables (available here): Last update: 24/11/09
  • Once inside your DMBS, simply restore the full backup of the database (this is for MS SQL Server 2008 only; a step-by-step walkthrough can be found here) or import the data from the tables to the database.
  • Congratulations! GeNS is now ready to be used.

b) Using the Web Services

The Web Services are now available here. Furthermore, a detailed description is also available here (Updated March 24).The Web Services API is in an early stage of development and, as such, users should bear in mind that certains problems may arise during it’s usage.

Advantages

  • Easy to understand and use
  • Flexible and scalable
  • Efficient
  • Accessible by several methods
  • Improves the cross-database low identifier coverage issue

Architecture

GeNS uses four distinct methods for gathering data from external databases: by Web Services, web crawlers, database connectors and finally by tabular files connectors. All of the recovered data is subsquently processed and synchronized to our database. Finally, the data can be accessed via Web Services or by downloading, installing and querying the data with SQL.

Currently, GeNS is importing data from four major databases: UniProt (SwissProt and TrEMBL), KEGG, EMBL – EBI and Entrez. Since these databases already incorporate data from third-party databases, we have over 460.000 unique genes, more than 100.000 biological relations and a hundred and forty distinct datatypes.

Architecture

Architecture

Database

GeNS database was designed with simplicity and extensibility in mind; the following schema is a complete representation of the database.

Database

Database

Concepts:

  • Organism: An individual form of life capable of growing, metabolizing nutrients, and usually reproducing. Organisms can be unicellular or multicellular. The Organism table stores taxonomic information; each entry corresponds to an organism with any given number of associated proteins. This table is the root of the hierarchical model. For each organism, we store its scientific and short names.
  • Protein: Any of a group of complex organic macromolecules that contain carbon, hydrogen, oxygen, nitrogen, and usually sulfur and are composed of one or more chains of amino acids. The Protein table is where the proteins’ internal identifiers and gene locus are stored; each entry in this table has a referring organism (in which this protein is found) and may have any number of associated biological entities and/or equivalent external databases’ protein identifiers in the ProteinIdentifier and BioEntity tables.
  • ProteinIdentifier: The table in which the mapping between the external databases’ protein identifier and BioPortal’s
    internal identifier is made.
  • BioEntity:  A table that stores all the biological entities associated with a given protein; this includes,
    among other things, pathways and gene ontologies.
  • DataType: A table listing all the possible external databases from which the biological data may come from; each entry in the ProteinIdentifier and BioEntity tables references this
    table, so that we may easily determine the nature (and source) of the
    data.

Reproducing the results

The following files allow anyone to reproduce the obtained results regarding the cross-database low identifier coverage issue and the
performance testing queries. You will need a working copy of GeNS in order to use these scripts.

GeneBrowser

GeneBrowser is a web-based tool that, for a given list of genes, combines data from several public databases with visualisation and analysis methods to help identify the most relevant and common biological characteristics. The functionalities provided include the following: a central point with the most relevant biological information for each inserted gene; a list of the most related papers in PubMed and gene expression studies in ArrayExpress; and an extended approach to functional analysis applied to Gene Ontology, homologies, gene chromosomal localisation and pathways.

GeneBrowser

GeneBrowser

Although GeneBrowser can be used to answer many different biological questions, a particular question set was used to tune its development:

  • What public databases provide relevant information about my dataset and how can I navigate through them?
  • What biological processes are enriched with respect to my input list of genes?
  • What are the most relevant metabolic pathways that contain my genes?
  • What are the genomic regions of these genes?
  • Which are the most relevant homologue classes in my list of genes?
  • What gene expression experiments have been previously conducted with the same genes?
  • What are the most relevant publications associated with my study?

Feedback

We highly appreciate any feedback you can provide regarding GeneBrowser. jpa@ua.pt. Thank you.

Reference

J. Arrais, J. Fernandes, J. Pereira and J. L. Oliveira, Exploring and identifying common biological traits in a set of genes, BMC Bioinformatics, BMC Bioinformatics 2010, 11:212 (link)

Dicoogle

Dicoogle is an information retrieval system for medical images. It starts by indexing DICOM files and metadata, both locally and in distributed systems using a P2P communication framework. Upon this distributed index users can then search for exams or specific features using a free text interface.

QuExT

What is QuExT?

QuExT (Query Expansion Tool) is a document indexing and retrieval application that obtains, from the MEDLINE database, a ranked list of publications that are most significant to a particular set of genes. Document retrieval and ranking are based on a concept-based methodology that broadens the resulting set of documents to include documents focusing on these gene-related concepts. Each gene in the input list is expanded to its various synonyms and to a network of biologically associated terms. Currently, the expansion is based on proteins, metabolic pathways and diseases (this last one only when the selected organism is Homo sapiens). The retrieved documents are ranked according to user-definable weights for each of these concept classes. By simply changing these weights, users can alter the order of the documents, allowing them to obtain for example, documents that are more focused on the metabolic pathways in which the initial genes are involved, rather than on the genes themselves.

How does it work?

QuExT receives as input a list of genes and a corresponding organism. The gene list can be typed into the input box or uploaded in a text file. Genes can be separated by commas or spaces. The organism to consider is selected from the drop-box menu. Figure 1 shows the query expansion procedure.

When the user submits the form, gene names or identifiers in the input are checked against a database and mapped to an internal identifier corresponding to the selected organism. Genes which are not found in the database are rejected from further analysis.

QuExT then creates an expanded query and searches a local index of the PubMed database for documents matching this query.

Query expansion is performed as follows: for each gene in the query, the algorithm obtains, from a term expansion table corresponding to the selected organism, all the alternative gene, protein, pathway and disease names corresponding to that gene’s internal ID. The full list of terms from all input genes is then accumulated in four separate query strings (one for each concept type). Each term obtained from expanding all genes is used to search the index.

QuExT runs four index searches using the four query strings obtained in the query expansion stage (one for each concept type). For each search, the documents that match the query and the corresponding scores are obtained. Resulting documents and corresponding scores are kept on separate lists, one for each concept class.

Notice that while the term expansion takes into account the selected organism, to avoid going from a gene in one organism to a related term in a different organism, this is not true for document retrieval. Since the indexing does not distinguish between different species referred in the articles, a search for a gene name in H. sapiens may return results referring to the same gene but in mice, for example.

Finally, the results from the document retrieval stage are assembled and documents are re-ranked in terms of the defined weights for each concept. The final score for document i is obtained as a weighted sum of the four concept-based scores:

score

where Wj is the weight attributed to the concept type j and sij represents the score for document i in terms of the jth concept type.

References

S. Matos, J. P. Arrais, J. Maia-Rodrigues, J. L. Oliveira, “Concept-based query expansion for retrieving gene related publications from MEDLINE”, BMC Bioinformatics, Apr 28; 11:212, 2010.

Neoscreen

NeoScreen is a bioinformatics software that helps diagnosis tasks in newborn screening programs. The application imports MS/MS raw data, and organizes and maintains all the information along the time in a database, providing a set of patterns that allow the detection of abnormalities in the blood samples. Is is been used, from 2005, to support the Portuguese Newborn Screning Program (http://www.diagnosticoprecoce.org/)

NeoScreen – Newborn screening analysis

The introduction of the Tandem Mass Spectrometry (MS/MS) in neonatal screening laboratories has opened the way to innovative newborn screening analysis. With this technology the number of metabolic disorders that can be detected, from dried blood-spot species, increases significantly. However, the amount of information obtained with this technique and the pressure for quick and accurate diagnostics raises serious difficulties in the daily data analysis. To face this challenge we developed a software system, NeoScreen, which simplifies and allow speeding up newborn screening diagnostics.

Software

In this view, the individuals are separated in several diagnostic categories, such as “very suspicious”, “suspicious”, “not suspicious”, etc. Some of these categories represent individuals with markers out of the established limits, but that are not associated with any known disease. In the right-side frame it is displayed the relevant information that was extracted and processed by the software for each individual, like: plate information, markers concentrations, and suspicious diseases.

Neoscreen

Neoscreen

Since May 2011, NeoScreen is represented by BMD Software Lda.
Mind

MIND is a repository of microarray experiments that handles storage, management and analysis of microarray data. It is supported by an infrastructure prepared to integrate dynamically further functionalities (Quality Control assurance, data processing, data mining, visualization, reports, etc.).

Microarray INformation Database

WEB site

The development of microarray technology has been phenomenal during the past years, and it is becoming a daily tool in many genomics research laboratories. However, the multi-step and data-intensive nature of this technology has created an unprecedented computational challenge. In fact, the full power of microarrays technology can only be achieved if researchers are able to efficiently store, analyse and share their results.

MIND Workflow

MIND Workflow

LIMS capabilities

A LIMS (Laboratory Information Management System) is an database repository that allows to manage all the laboratorial data.

MIND LIMS

MIND LIMS

Main advantages of MIND:

  • Easier and fast access to all the laboratorial data
  • Trace of all the experiment allowing errors detection
  • Allows an easier share of data among different users
  • Public web-based interface
  • MIAME and MAGE compliance

Data Analysis capabilities

MIND Data Analysis

MIND Data Analysis

Quality control

  • Enables the user to detect systematic errors on the production of microarrays. It also allows the usage of some pre-processing such as background subtraction, data normalization and data filtering;

Exploratory data analysis

  • Allows the user to, based on definite objectives, specify the experiment design and retrieve the biological meaning from the shown results.

Software integration

  • Allow the dynamic introduction of processing algorithms and R scripts.

Publications

  • J. Arrais, J. L. Oliveira, G. Grimes, S. Moodie, K. Robertson, and P. Ghazal, “Microarray data sharing in BioMedicine”, in The XX International Congress of the European Federation for Medical Informatics (MIE’2006), Maastricht, Netherlands, 2006.
  • J. Arrais, L. Carreto, M. A. S. Santos, and J. L. Oliveira, “Collaborative work on microarrays using MAGE-ML”, in 9th International Meeting of the Microarray Gene Expression Data Society (MGED9), Seattle, Washington, USA, 2006.
Anaconda

ANACONDA is a software package specially developed for the study of genes’ primary structure. It uses gene sequences downloaded from public databases, as FASTA and GenBank, and it applies a set of statistical and visualization methods in different ways, to reveal information about codon context, codon usage, nucleotide repeats within open reading frames (ORFeome) and others.

Codon context analysis

Genome sequencing is opening unprecedent ways for understanding how gene primary structure is organized. Two of the most studied open reading frame characteristics are codon usage and codon context.
Traditional methods used for codon usage and context analysis do not provide user-friendly tools to carry out detailed gene primary structure analysis at a genomic scale.

Codon usage tables, using absolute metric, are available in public databases for any sequenced gene or genome and freeware software for multivariate analysis (correspondence analysis) of codon and amino acid usage is also readily available, however sophisticated statistical and data visualization tools are clearly lacking.

We propose the usage of several statistical methods – contingency table analysis, residual analysis, multivariate analysis (cluster analysis) – to analyze the codon bias under various aspects (degree of association, contexts and clustering).

Cluster analysis

A cluster analysis tool allows also calculating similarities between two vectors of the contingency table. This technique is used to group lines and columns (codons) of the correlation matrix, allowing highlight global patterns in the genes.

The statistical tools that are incorporated in the system, for data clustering, residual analysis and histogram plotting of calculated indexes, allow reaching new conclusions on gene primary structure features at a genomic scale. We expect that the results obtained will permit identifying some general rules that govern codon context and codon usage in any genome. Additionally, the identification of genes containing expanded codons that arise as a consequence of erroneous DNA replications events will permit uncovering new genes associated to human disease.

Visualization

In order to detect the impact of codon context bias (as well as the presence of rare codons) on coding sequences, ANACONDA has additional tools for sequence mapping. The layout for sequence include written information about the ORF and the sequence itself, in which the codons have been coloured with the same residual colour scale of the ORFeome map.

ANACONDA allows the user to work with more than one ORFeome at a time. This creates large data sets that are difficult to deal with, in particular when multiple comparisons are being performed.

Considering that vast number of ORFeomes can be analyzed simultaneously by ANACONDA, we have included extra tools to allow comparative studies.

Anaconda

Anaconda

he statistical tools that are incorporated in the system, for data clustering, residual analysis and histogram plotting of calculated indexes, allow reaching new conclusions on gene primary structure features at a genomic scale. We expect that the results obtained will permit identifying some general rules that govern codon context and codon usage in any genome.

Past publications

  • G. Moura, M. Pinheiro, J. Arrais, A. C. Gomes, L. Carreto, A. Freitas, J. L. Oliveira, and M. A. Santos, “Large Scale Comparative Codon-Pair Context Analysis Unveils General Rules that Fine-Tune Evolution of mRNA Primary Structure”, PLoS ONE, vol. 2, no. 9, e847, doi:10.1371/journal.pone.0000847, 2007.
  • M. Pinheiro, V. Afreixo, G. Moura, A. Freitas, M. A. Santos, and J. L. Oliveira, “Statistical, computational and visualization methodologies to unveil gene primary structure features”, Methods of Information in Medicine, vol. 45, no. 2, pp. 163-168, 2006.
  • G. Moura, M. Pinheiro, R. Silva, I. Miranda, V. Afreixo, G. Dias, A. Freitas, J. L. Oliveira, and M. A. Santos, “Comparative context analysis of codon pairs on an ORFeome scale”, Genome Biology, vol. 6, no. 3, pp. R28, 2005.

Download

Anaconda 2 is now available for download. It is freely available for fundamental research only.
[Download]

Last Update (2011-01-12)

New features (Version 2.0, 2011):

  • Corrected some bugs
  • Enriched codon statistics and visualization maps
  • Comparing context maps across several species
  • Integration of tRNA copy number processing
  • Single and multiple sequence alignments using codon context (BLASTP and  ClustalW)
Himage PACS
A PACS solution for echocardiography laboratories that provides a cost-efficient digital archive, and enables the acquisition, storage, transmission and visualization of DICOM cardiovascular ultrasound sequences.

Scenario

The medical imaging digitalization and implementation of PACS (Picture Archiving and Communication Systems) systems increases practitioner’s satisfaction through improved faster and ubiquitous access to image data. Besides, it reduces the logistic costs associated to the storage and management of image data and also increases the intra and inter institutional data portability. Echocardiography is a rather demanding medical imaging modality when regarded as digital source of visual information. The date rate and volume associated with a typical study poses several problems. They are hard to keep “online” (in centralized servers) and difficult to access (in real-time) outside the institutional broadband network infra-structure. For example, an uncompressed echocardiography study size can typically vary between 100 and 500Mbytes.

Product Presentation

The innovation of our approach is the implementation of a DICOM private transfer syntax designed to support any video encoder installed on the operating system. This structure provides great flexibility concerning the selection of an encoder that best suits the specifics of a particular imaging modality or working scenario. To ultrasound studies we are using the highly efficient MPEG4 codec that takes full advantage of object texture, shape coding and inter-frame redundancy. More than 40.000 studies have been performed so far. For example, a typical Doopler color run (RGB) with an optimized time-acquisition (15-30 frames) and a sampling matrix (480*512), rarely exceed 200-300kB. Typical compression ratios can go from 65 for a single cardiac cycle sequence to 100 in multi- cycle sequences. With these averaged figures, even for a heavy work-loaded echolab, it is possible to have all historic procedures online or distribute them with reduced transfer time over the network, which is a very critical issue when dealing with costly or low bandwidth connections. The solution is actually installed in one public Central Hospital (CHVNG) and one private laboratory of cardiac images. Because the solution front-end is fully Web-based, the clinical specialists are using the platform to provide decision support remotely, accessing over Internet in a secure way (i.e. over SSL). Moreover, the solution is changing the work methods. The process workflow is fully digital where reviewing and reporting procedures can be done at physician’s home (i.e. telework).

MS-PDC
MS-PDC

Himage Modules

  • Visualization – view dicom medical images
  • Report Module – edit and export a image report, with customizable layout, to Word.
  • Burning Module – to export the study to CD/DVD in DICOM default transfer syntax, including a standalone viewer.
  • Communications Module – send a study to a external server.
HImage Modules

Himage Modules

Image Quality

Two studies were carried on assessing the DICOM cardiovascular ultrasound image quality. In a simultaneous and blind display of the original against the compressed cine-loops, 37% of the trials have selected the compressed sequence as the best image. This suggests that other factors related with viewing conditions are more likely to influence observer performance than the image compression itself.

Developing new tools for studying mRNA mistranslation

Funding entity: FCT (PTDC/BIA-BCM/72251/2006)
Period: 2008-2011

Implementation of a Nacional Facility for DNA Microarrays: Phase II

Funding entity: FCT (PTDC/BIA-BCM/64745/2006)
Period: 2009-2011

New statistical methodologies for analysis DNA microarrays data

Funding entity: FCT (PTDC/MAT/72974/2006)
Period: 2006-2008

DNA Microarray technology is one of the most promising new technologies for global gene expression analysis. This technology is sophisticated, very expensive, highly interdisciplinary and produces vast amounts of data whose management and analysis pose significant challenges. This project aims to study new bi-clustering approaches that can help to obtain relevant information from gene expression microarrays.

mRNA mistranslation in yeast

Funding entity: HFSP Research Grant
Period: 2005-2008

The very few quantitative mRNA mistranslation studies carried out to date indicate that the average decoding error ranges from 10-4 to 10-5 errors per codon decoded. However, no systematic study has yet been carried out to rank mRNA sequences according to
decoding error and no methodology has yet been developed to identify genes that are prone to decoding error.

In this project, software tools for data visualization and mathematical methodologies for identification of general rules governing  RNA translation, and tools for mapping mRNA regions of high decoding error and for identifying putative gene expression regulatory sequences present in mRNAs, will be developed.

INFOBIOMED – Structuring European Biomedical Informatics to Support Individualised Healthcare

Funding entity: IST FP6 (IST2002-507585) – NoE (Network of Excelence)
Period: 2003-2006

There is a great potential for synergy between medical informatics and bioinformatics with a view on continuity and individualisation of healthcare, so that the benefits of the human genome sequence can reach the population. A collaborative effort between those two disciplines is needed to bridge the current gap between them. Biomedical Informatics (BMI) is an emerging discipline that aims at bringing these two worlds together to foster the development of novel diagnostic and therapeutic methodologies and strategies.

The INFOBIOMED network aims at setting a durable structure for the described collaborative approach at an European level, mobilising the critical mass and the resources necessary for enabling the collaborative approach that supports the consolidation of BMI as a crucial scientific discipline for future healthcare.
(http://www.infobiomed.org/)

An eHealth Successful Project

INFOGENMED – A virtual laboratory for accessing and integrating genetic and medical information for health applications

Funding entity: IST FP5 (IST2001-39013)
Period: 2002-2004

UA/IEETA was the Project Coordinator

One goal currently challenging bio – and clinical informatics is to develop robust computational methods and tools to model, store, retrieve and analyse information at multiple levels of complexity, i.e., from molecule to organism. For example, the unification of heterogeneous databases under one virtual system is an important step towards developing such robust computational models. The latter is the objective of the INFOGENMED project which aims at building a virtual laboratory for accessing and integrating genetic and medical information for health applications. Once built, the system allows practitioners, biologists, chemists and other experts to navigate through local and remote biomedical databases.

INFOGENMED started in September 2002, (http://www.infogenmed.net), and the functionalities already built in the system allow for: (1) defining clinical pathways to guide the user in the navigation of multiple sources over the Internet; (2) identifying and characterizing the most relevant databases to support the molecular medicine practice for selected rare genetic diseases; (3) designing the integration methods, based on virtual databases, mediators and semantic vocabulary servers.

Next Generation Information Systems
2011/01/27
11:15to12:15

Talk from Florentino Fernández Riverola, Dpto. de Informática – Universidade de Vigo
Current research lines and projects of the “Next Generation Information Systems” group, from University of Vigo, in Orense

14th Annual Meeting of the Portuguese Human Genetics Society
2010/10/18

A 14ª Reunião da Sociedade Portuguesa de Genética Humana irá realizar-se nos dias 18, 19 e 20 de Novembro de 2010, em Coimbra, no Auditório da Fundação Bissaya Barreto (Bencanta).

Mais informação na página da SPGH.

ITAB2010
2010/11/02to2010/11/05

The 10th IEEE International Conference on Information Technology and Applications in Biomedicine,
will be held in Corfu, Greece, November 2-5, 2010 at Aquis Corfu Holiday Palace.

X Jornadas Bioinformática 2010
2010/10/26to2010/10/29

The Xth Spanish Symposium on Bioinformatics (JBI2010) take place in October 27-29, 2010 in Torremolinos-Málaga, Spain. Co-organised by the National Institute of Bioinformatics-Spain and the Portuguese Bioinformatics Network and hosted by the University of Malaga (Spain).

23rd tRNA Workshop, Jan 2010

Place: Aveiro, Portugal
Date:
28 Jan- 2 Feb 2010

http://www.trna2010.com/

XV National Congress of Biochemistry (NCB2006)

Place: Aveiro, Portugal
Date:
December 8-10, 2006

http://www.ieeta.pt/ncb2006

IV International Symposium on Biological and Medical Data Analysis (ISBMDA 2005)

Place: Aveiro, Portugal
Date:
November 10-11, 2005

http://www.ieeta.pt/isbmda05

Books and Chapters

Books

  • M. Santos (Ed.)
    XVth National Congress of Biochemistry, 2006
    ISBN 978-972-789-214-3
  • M. Santos (Ed.)
    IIIrd National Meeting on RNA Biology, 2006
    ISBN 978-972-789-215-0
  • J. L. Oliveira, V. Maojo, F. Martin-Sanchez, and A. S. Pereira (Eds.),
    Biological and Medical Data Analysis, Springer, 2005,
    ISBN 978-972-789-215-0, http://www.springerlink.com/content/k15u6315h070/

Book chapters

  • C. V. Ferreira, C. Costa
    “Challenges of Using Cloud Computing in Medical Imaging”
    in Advances in Cloud Computing Research, M. Ramachandran, 2014.
  •  J. Melo, J. P. Arrais, E.Coelho, P. Lopes, N. Rosa, M. J. Correia, M.Barros and J. L. Oliveira
    “Data Integration Solution for Organ-Specific Studies: An Application for Oral Biology”
    in Biomedical Engineering Systems and Technologies, J. Gabriel, J. Schier, S. Huffel et al, Eds., Springer Berlin Heidelberg, 2013.
  • A. Freitas, W. Ayadi, M. Elloumi, J. L. Oliveira, and J.-K. Hao
    “A Survey on Biclustering of Gene Expression Data”
    in Biological Knowledge Discovery Handbook: Preprocessing, Mining and Postprocessing of Biological Data, M. Elloumi & A. Zomaya, Eds., Wiley, 2013.
  • D. Campos, S. Matos, and J. L. Oliveira
    “Current methodologies for biomedical Named Entity Recognition”
    in Biological Knowledge Discovery Handbook: Preprocessing, Mining and Postprocessing of Biological Data, M. Elloumi & A. Zomaya, Eds., Wiley, 2013.
  • M. Santos, L. Bastião, C. Costa, A. Silva, N. Rocha
    “Clinical Data Mining in Small Hospital PACS: Contributions for Radiology Department Improvement”
    in Information Systems and Technologies for Enhancing Health and Social Care, IGI Global, 2013.
  • F. Valente, C. Costa, and A. Silva
    “Content Based Retrieval Systems in a Clinical Context”
    in Medical Imaging in Clinical Practice, Okechukwu F. Erondu, Ed., InTech, February 2013.
  • D. Campos, S. Matos, and J. L. Oliveira
    “Biomedical Named Entity Recognition: a Survey of Machine-Learning Tools”
    in Theory and Applications for Advanced Text Mining, S. Sakurai, Ed., InTech, 2012.
  • P. Lopes and J. L. Oliveira
    “Collecting and Enriching Human Variome Datasets”
    in Tecnologías NBIC en Salud: El papel protagonista de la Nanociencia, J. Aguiló, A. Freire, D. Iglesia, V López, A Pazos, Eds., CYTED, 2012, pp. 9-19.
  • L. S. Ribeiro, C. Costa and J. L. Oliveira
    “Current Trends in Archiving and Transmission of Medical Images”
    in Medical Imaging, Okechukwu F. Erondu, Ed., InTech, December 2011.
  • J. Arrais, S. Matos, and J. L. Oliveira
    “Integração de Dados Biomédicos”
    in Nano, Bio, Info y Cogno (Convergencia de Tecnologías NBIC) Conceptos y Aplicaciones, J Aguiló, A Freire, D Iglesia, F Martin, A Pazos, Eds., 2011, pp. 185-226.
  • G. Moura, M. Pinheiro, A. Freitas, J. L. Oliveira, and M. A. Santos
    “Computational and Statistical Methodologies for ORFeome Primary Structure Analysis”
    in Comparative Genomics, Methods in Molecular Biology series, N. Bergman, Ed.: Humana Press, USA, 2007, pp. 449-462.
  • C. Costa, A. Silva, and J. L. Oliveira
    “Current Perspectives on PACS and a Cardiology Case Study”
    in Advanced Computational Intelligence Paradigms in Healthcare 2, vol. 65, S. Vaidya, L. C. Jain, and H. Yoshida, Eds.: Springer-Verlag, 2007, pp. 79-108.
  • C. Costa, A. Silva, J. L. Oliveira, V. Ribeiro, and J. Ribeiro
    “A demanding Web-based PACS supported by Web Services technology”
    in Medical Imaging 2006: PACS and Imaging Informatics, vol. 6145, O. R. Steven C.Horii, Ed., 2006.
  • C. Costa, J. L. Oliveira, A. Silva, V. Ribeiro, and J. Ribeiro
    “Himage: Um Web-PACS inovador para Imagem Cardíaca”
    in TIC em Biomedicina, vol. 6145, M. G. J. R. Rabunal, N. Pedreira, J. Pereira, Ed. Santiago de Compostela 2005.
Journals
  • E. Coelho, J. Arrais, S. Matos, C. Pereira, N. Rosa, M. Correia, M. Barros, and J. Oliveira
    “Computational prediction of the human-microbial oral interactome”
    BMC Systems Biology, 2014. pdf
  • V. M. Prieto, S. Matos, M. Álvarez, F. Cacheda, J. L. Oliveira
    “Twitter: A Good Place to Detect Health Conditions.”
    PLoS ONE, 2014. pdf
  • M. Reboiro-Jato, J. Arrais, J. L. Oliveira, F. Fdez-Riverola
    “geneCommittee: a web-based tool for extensively testing the discriminatory power of biologically relevant gene sets in microarray data classification”
    BMC Bioinformatics, 2014. pdf (highly accessed)
  • D. Campos, Q. C. Bui, S. Matos, and J. L. Oliveira
    “TrigNER: automatically optimized biomedical event trigger recognition on scientific documents”
    Source Code Biol Med, vol. 9, p. 1, Jan 2014. pdf
  • P. Lopes, T. Nunes, D. Campos, L. Furlong, A. Bauer-Mehren, F. Sanz, M. C. Carrascosa, J. Mestres, J. Kors, B. Singh, E. van Mulligen, J. Van der Lei, G. Diallo, P. Avillach, E. Ahlberg, S. Boyer, C. Diaz, J. L. Oliveira
    “ Gathering and Exploring Scientific Knowledge in Pharmacovigilance”
    PLoS ONE, 2013. pdf
  • L. Ribeiro, C. Viana-Ferreira, J. L. Oliveira, C. Costa,
    “ XDS-I outsourcing proxy: ensuring confidentiality while preserving interoperability”
    IEEE Journal of Biomedical and Health Informatics, 2013. pdf
  • P. Gaspar, P. Lopes, J. Oliveira, R. Santos, R. Dalgleish, J. L. Oliveira
    “Variobox: Automatic Detection and Annotation of Human Genetic Variants”
    Human Mutation , 2013. pdf
  • L. Bastião, R. Pinho, L. Ribeiro, C. Costa, J. L. Oliveira
    “A Centralized Platform for Geo-Distributed PACS Management”
    Journal of Digital Imaging , 2013. pdf
  • S. Matos, H. Araújo, J. L. Oliveira
    “Biomedical literature exploration through latent semantics”
    Advances in Distributed Computing and Artificial Intelligence Journal , 2013. pdf
  • L. A. Campos, V. L. Pereira Jr., A. Muralikrishna, S. Albarwani, S. Brás, S. Gouveia
    “Mathematical Biomarkers for the Autonomic Regulation of Cardiovascular System”
    Frontiers in Integrative Physiology, 2013. pdf
  • D. Campos, S. Matos, J. L. Oliveira
    “A modular framework for biomedical concept recognition”
    BMC Bioinformatics, 14:281, 2013. pdf (highly accessed)
  • P. M. Coloma, M. J. Schuemie, G. Trifirò, L. Furlong, E.van Mulligen, A. Bauer-Mehren, P. Avillach, J. Kors, F. Sanz, J. Mestres, J. L. Oliveira, S. Boyer, E. A. Helgee, M. Molokhia, J. Matthews, D. Prieto-Merino, R. Gini, R. Herings, G. Mazzaglia, G. Picelli, L. Scotti, L. Pedersen, J. van der Lei, M. Sturkenboom
    “Drug-Induced Acute Myocardial Infarction: Identifying ‘Prime Suspects’ from Electronic Healthcare Records-Based Surveillance System”
    PLOS ONE , 2013. pdf
  • P . Lopes. J. L. Oliveira
    “An innovative portal for rare genetic diseases research: The semantic Diseasecard”
    Journal of Biomedical Informatics, 2013. pdf
  • M. Cases, L. I. Furlong, J. Albanell, R. B. Altman, R. Bellazzi, S. Boyer, A. Brand, A. J. Brookes, S. Brunak, T. W. Clark, J. Gea, P. Ghazal, N. Graf, R. Guigó, T. E. Klein, N. López-Bigas, V. Maojo, B. Mons, M. Musen, J. L. Oliveira, A. Rowe, P. Ruch, A. Shavo, E. H. Shortliffe, A. Valencia, J. v. d. Lei, M. A. Mayer, and F. Sanz
    “How to improve data and knowledge management to better integrate healthcare and research”
    Journal of Internal Medicine, 2013. pdf
  • T. Nunes; D. Campos; S. Matos; J. L. Oliveira
    “BeCAS: biomedical concept recognition services and visualization”
    Bioinformatics,, 2013. pdf
  • F. Valente, C. Costa, and A. Silva
    “Dicoogle, a PACS featuring Profiled Content Based Image Retrieval”
    PLoS ONE, 2013. pdf
  • J. Arrais, N. Rosa, J. Melo, E. Coelho, D. Amaral, M. J. Correia, M. Barros, and J. L. Oliveira
    “OralCard: a bioinformatic tool for the study of Oral Proteome”
    Archives of Oral Biology, Feb 2013. pdf
  • D. Campos, S. Matos, and J. L. Oliveira
    “Gimli: open source and high-performance biomedical name recognition”
    BMC Bioinformatics, 14:54, Feb 2013.pdf (highly accessed)
  • P. Gaspar, G. Moura, M. A. S. Santos, and J. L. Oliveira
    “mRNA secondary structure optimization using a correlated stem-loop prediction”
    Nucleic Acids Research, Jan 2013.pdf
  • N. Yousaf, W. Monteiro, S. Matos, S. Birring, I. D. Pavord
    “Cough frequency in health and disease”
    European Respiratory Journal, vol. 41, no. 1, p. 241-243, Jan 2013. pdf
  • P. Lopes and J. L. Oliveira
    “COEUS: “semantic web in a box” for biomedical applications”
    Journal of Biomedical Semantics, vol. 3, Dec 2012.pdf (highly accessed)
  • J. L. Oliveira, P. Lopes, T. Nunes, D. Campos, S. Boyer, E. Ahlberg, E. van Mullingen, J. Kors, B. Singh, L. I. Furlong, F. Sanz, A. Bauer-Mehren, M. D. C. Carrascosa, J. Mestres, P. Avillach, C. Díaz Acedo, and J. van der Lei
    “The EU-ADR Web Platform: delivering advanced pharmacovigilance tools”
    Pharmacoepidemiology and Drug Safety, vol. (online first), Dec 2012.pdf
  • J. P. Lousado, J. L. Oliveira, G. Moura, and M. A. S. Santos
    “An integrative approach for codon repeats evolutionary analyses”
    Int. J. of Data Mining and Bioinformatics, vol. 6, pp. 369-381, Sep 2012. pdf
  • C. Costa and J. L. Oliveira
    “Telecardiology through ubiquitous Internet services”
    International Journal of Medical Informatics, vol. 81, pp. 612-21, Sep 2012. pdf
  • L. Bastião, C. Costa, and J. L. Oliveira
    “DICOM Relay over the Cloud”
    International Journal of Computer Assisted Radiology and Surgery, vol. (online first), August 2012. pdf
  • P. Gaspar, J. L. Oliveira, J. Frommlet, M. A. S. Santos, and G. Moura
    “EuGene: Maximizing synthetic gene design for heterologous expression”
    Bioinformatics, vol. 28, Jul, 2012. pdf
  • K. K. Lee, A. Savani, S. Matos, D. H. Evans, I. D. Pavord, S. Birring
    “4-hour cough frequency monitoring in chronic cough”
    Chest, July, 2012. pdf
  • L. Ribeiro, C. Costa, and J. L. Oliveira
    “Clustering of distinct PACS archives using a cooperative peer-to-peer network”
    Computer Methods and Programs in Biomedicine, June 2012 pdf
  • F. Valente, C. Viana-Ferreira, C. Costa, and J. L. Oliveira
    “A RESTful Image Gateway for Multiple Medical Image Repositories”
    IEEE Transactions on Information Technology in BioMedicine, vol. 16, no. 3, pp. 356-36, 2012 pdf
  • D. Campos, S. Matos, I. Lewin, J. L. Oliveira, and D. Rebholz-Schuhmann
    “Harmonisation of gene/protein annotations: towards a gold standard MEDLINE”
    Bioinformatics, 2012. pdf
  • A. Bauer-Mehren, E. van Mullingen, P. Avillach, M. D. C. Carrascosa, R. García-Serna, J. Pinero, B. Singh, P. Lopes, J. L. Oliveira, G. Diallo, A. E. Helgee, B. Scott, J. Mestres, F. Sanz, J. Kors, and L. I. Furlong
    “Automatic filtering and substantiation of drug safety signals”
    PLoS Computational Biology, 2012. pdf
  • P. Gaspar, J. L. Oliveira
    “Advantages of a Pareto-based genetic algorithm to solve the gene synthetic design problem”
    Current Bioinformatics, vol. 7, no. 4, 2012.
  • S.C. Novais, T. Vandenbrouck, P. Lopes, J. Arrais, W. De Coen, A. Soares and M. Amorim
    “Enchytraeus albidus microarray: enrichment, design, annotation and database (EnchyBASE)”
    PLoS ONE, 2012. pdf
  • N. Rosa, M. J. Correia, J. Arrais, P. Lopes, J. Melo, J. L. Oliveira, and M. Barros
    “From the salivary proteome to the OralOme: Comprehensive molecular oral biology”
    Archives of Oral Biology, 2012 pdf
  • P. Grynberg, T. Abeel, P. Lopes, G. Macintyre, L. P. Rubiño
    “Highlights from the Student Council Symposium 2011 at the International Conference on Intelligent Systems for Molecular Biology and European Conference on Computational Biology”
    BMC Bioinformatics, 12, no. Suppl 11:A1, 21 November 2011 pdf
  • G. Moura, M. Pinheiro, A. Freitas, J. L. Oliveira, J. Frommlet, L. Carreto, A. R. Soares, A. R. Bezerra, and M. A. S. Santos
    “Species-Specific Codon Context Rules Unveil Non-Neutrality Effects of Synonymous Mutations”
    PLoS ONE, vol. 6, 2011. pdf
  • J. P. Arrais and J. L. Oliveira
    “Using biomedical networks to prioritize gene–disease associations”
    Open Access Bioinformatics, vol. 3, 2011. pdf
  • Z. Lu, H.-Y. Kao, C.-H. Wei, M. Huang, J. Liu, C.-J. Kuo, C.-N. Hsu, R.T.-H. Tsai, H.-J. Dai, N. Okazaki, H.-C. Cho, M. Gerner, I. Solt, S. Agarwal, F. Liu, D. Vishnyakova, P. Ruch, M. Romacker, F. Rinaldi, S. Bhattacharya, P. Srinivasan, H. Liu, M. Torii, S. Matos, D. Campos, K. Verspoor, K.M. Livingston, W.J. Wilbur
    “The Gene Normalization Task in BioCreative III”
    BMC Bioinformatics, vol. 12, no. Suppl 8, p. S9, September 2011 pdf
  • M. Krallinger, M. Vazquez, F. Leitner, D. Salgado, A. Chatraryamontri, A. Winter, L. Perfetto, L. Briganti, L. Licata, M. Iannuccelli, L. Castagnoli, G. Cesareni, M. Tyers, G. Schneider, F. Rinaldi, R. Leaman, G. Gonzalez, S. Matos, S. Kim, W.J. Wilbur, L. Rocha, A.V. Tendulkar, A. Rangrej, V. Raut, S. Agarwal, F. Liu, X. Wang, R. Rak, K. Noto, C. Elkan, Z. Lu, R. I. Dogan, Jean-F. Fontaine, M.A. Andrade-Navarro, A. Valencia
    “The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text”
    BMC Bioinformatics, vol. 12, no. Suppl 8, p. S9, September 2011 pdf
  • S. Matos and J. L. Oliveira
    “Classification methods for finding articles describing protein-protein interactions in PubMed”
    Journal of Integrative Bioinformatics, vol. 8, p. 178, 2011 pdf
  • M. Brochhausen, A. Burgun, W. Ceusters, A. Hasman, T. Y. Leong, M. Musen, J. L. Oliveira, M. Peleg, A. Rector, and S. Schulz
    “Discussion of Biomedical Ontologies: Toward Scientific Debate”,
    Methods of Information in Medicine, vol. 50, pp. 217-236, 2011. pdf
  • L. Bastião, C. Costa, and J. L. Oliveira
    “A PACS archive architecture supported on Cloud services”
    International Journal of Computer Assisted Radiology and Surgery, 2011. pdf
  • P. Lopes, R. Dalgleish, and J. L. Oliveira
    “WAVe: web analysis of the variome”
    Human Mutation, 2011. pdf
  • A. Freitas, V. Afreixo, M. Pinheiro, J. L. Oliveira, G. Moura, and M. A. S. Santos,
    “Improving the Performance of the Iterative Signature Algorithm for the Identification of Relevant Patterns”
    Statistical Analysis and Data Mining, vol. 4, pp. 71-83, 2011. pdf
  • C. Costa, C. Ferreira, L. Bastião, L. Ribeiro, A. Silva, and J. L. Oliveira
    “Dicoogle – an Open Source Peer-to-Peer PACS”
    Journal of Digital Imaging, Oct 28, 2010. pdf
  • J. P. Arrais, J. Fernandes, J. Pereira, J.L. Oliveira
    “GeneBrowser 2: an application to explore and identify common biological traits in a set of genes”
    BMC Bioinformatics, Jul 21; 11:389, 2010. pdf (highly accessed)
  • S. Matos, J. P. Arrais, J. Maia-Rodrigues, J. L. Oliveira
    “Concept-based query expansion for retrieving gene related publications from MEDLINE”
    BMC Bioinformatics, Apr 28; 11:212, 2010. pdf (highly accessed)
  • N. Yousaf, W. Monteiro, D. Parker, S. Matos, S Birring, I D Pavord
    “Long-term low-dose erythromycin in patients with unexplained chronic cough: a double-blind placebo controlled trial”
    Thorax, vol. 65, no. 12, p. 1107-1110, December 2010 pdf
  • A. R. Soares, P. M. Pereira, B. Santos, C. Egas, A. C. Gomes, J. Arrais, J. L. Oliveira, G. Moura, and M. A. S. Santos
    “Parallel DNA pyrosequencing unveils new zebrafish microRNAs”
    BMC Genomics, vol. 10, 2009. pdf (highly accessed)
  • C. Costa, J. L. Oliveira, A. Silva, V. Ribeiro, and J. Ribeiro
    “Design, development, exploitation and assessment of a Cardiology Web PACS”
    Computer Methods and Programs in Biomedicine, vol. 93, pp. 273-282, 2009. pdf
  • C. Costa, F. Freitas, M. Pereira, A. Silva, and J. L. Oliveira
    “Indexing and retrieving DICOM data in disperse and unstructured archives”
    International Journal of Computer Assisted Radiology and Surgery, vol. 4, pp. 71-77, 2009. pdf
  • G. Moura, J. P. Lousado, M. Pinheiro, L. Carreto, R. Silva, J. L. Oliveira, and M. A. Santos
    “Codon-triplet context unveils unique features of the Candida albicans protein coding genome”
    BMC Genomics, vol. 8, no. 444, 2007. pdf
  • J. Arrais, B. Santos, J. Fernandes, L. Carreto, M. A. Santos, and J. L. Oliveira
    “GeneBrowser: an approach for integration and functional classification of genomic data”
    Journal of Integrative Bioinformatics, vol. 4, no. 3, 2007. pdf
  • G. Moura, M. Pinheiro, J. Arrais, A. C. Gomes, L. Carreto, A. Freitas, J. L. Oliveira, and M. A. Santos
    “Large Scale Comparative Codon-Pair Context Analysis Unveils General Rules that Fine-Tune Evolution of mRNA Primary Structure”
    PLoS ONE, vol. 2, no. 9, e847, doi:10.1371/journal.pone.0000847, 2007. pdf
  • D. Polónia, C. Costa, A. Silva, and J. L. Oliveira
    “PACS procurement planning and negotiation strategies for regional health institutions in the National Health Service of an EU country”
    International Journal of Computer Assisted Radiology and Surgery, Vol 2, Sup 1, 2007.
  • C. Costa, J. L. Oliveira, A. Silva, V. Gama, and J. Ribeiro
    “Enhanced PACS to support Demanding Telemedicine and Telework Scenarios”
    International Journal of Computer Assisted Radiology and Surgery, Vol 2, Sup 1, 2007.
  • M. Pinheiro, V. Afreixo, G. Moura, A. Freitas, M. A. Santos, and J. L. Oliveira
    “Statistical, computational and visualization methodologies to unveil gene primary structure features
    Methods of Information in Medicine, vol. 45, no. 2, pp. 163-168, 2006.
  • I. Oliveira, J. L. Oliveira, J. P. Sanchez, V. López-Alonso, F. Martin-Sanchez, V. Maojo, and A. S. Pereira
    “Grid requirements for the integration of biomedical information resources for health applications”
    Methods of Information in Medicine, vol. 44, no. 2, pp. 161-67, 2005.
  • G. Moura, M. Pinheiro, R. Silva, I. Miranda, V. Afreixo, G. Dias, A. Freitas, J. L. Oliveira, and M. A. Santos
    “Comparative context analysis of codon pairs on an ORFeome scale”
    Genome Biology, vol. 6, no. 3, pp. R28, 2005.

International Magazines

  • L. Bastião, C. Costa
    “Migrating PACS to the cloud – advantages and drawbacks”
    International Hospital and Equipment, March/April 2012, vol 38, p16-18
  • L. Bastião, C. Costa, and J. L. Oliveira
    “Strengths and Weaknesses of Using Cloud Computing”
    Imaging Management, vol. 11, 2012 pdf
  • C. Costa, L. Bastião, C. Ferreira, S. Campos, A. Silva, and J. L. Oliveira
    “Dicoogle – a paradigm change in medical imaging networks”
    Diagnostic Imaging Europe, pp. 22-23, November 2011 pdf
Conferences
  • F. Barbosa, J. Arrais and J.L. Oliveira, “Weighted Gene Co-expression Network Analysis Applied to Head and Neck Squamous Cell Carcinoma Data”, In  Proceedings of the International Conference on Health Informatics (ICHI 2013)Vilamoura, Portugal, 2013
  • L. Ribeiro, R. Rodrigues, C. Costa and J.L. Oliveira, “Enabling Outsourcing XDS for Imaging on the Public Cloud”, In  Proceedings of the 14th World Congress on Medical and Health Informatics (MEDINFO 2013). Copenhagen, Denmark, 2013
  • F. Marques, P. Azevedo, J. P. Cunha, M. B. Cunha, S. Brás, J. M. Fernandes, “IREMAN: FIRefighter team brEathing Management system using ANdroid”, In 17th International Symposium on Wearable Computers (ISWC). Zurich, Switzerland, 2013
  • S. Brás, J. M. Fernandes, J. P.S. Cunha, “ECG Delineation and Morphological Analysis for Firefighters Tasks Differentiation”, In Proceedings of the 26th International Symposium on Computer-Based Medical Systems (CBMS). Porto, Portugal, 2013
  • L. Ribeiro, R. Rodrigues, C. Costa and J.L. Oliveira, “Enabling outsourcing XDS for imaging on the public Cloud”, In 14th World Congress on Medical and Health Informatics (MEDINFO 2013). Copenhagen, Denmark, 2013.
  • Milton Santos, Luis Bastião, Carlos Costa, Augusto Silva, Nelson Rocha. “Multi Vendor DICOM Metadata Access: A Multi Site Hospital Approach Using Dicoogle”, in 8th Iberian Conference on Information Systems and Technologies (CISTI 2013), Lisboa, Portugal, 2013.
  • Tiago Godinho, Luís A. Bastião Silva, Carlos Viana-Ferreira, Carlos Costa and José Luís Oliveira. “Enhanced regional network for medical imaging repositories”, in 8th Iberian Conference on Information Systems and Technologies (CISTI 2013), Lisboa, Portugal, 2013.
  • J. C. Santos, T. Pedrosa, C. Costa, and J. L. Oliveira, ” Concepts for a Personal Health Record”, in 24th European Medical Informatics Conference (MIE 2012), Pisa, Italy, 2012.
  • C. Viana-Ferreira, D. Ferreira, F. Valente, E. Monteiro, C. Costa, and J. L. Oliveira, “Dicoogle Mobile: a medical imaging platform for Android”, in 24th European Medical Informatics Conference (MIE 2012), Pisa, Italy, 2012.
  • L. Ribeiro, C. Costa, and J. L. Oliveira, “Enhancing the many-to-many relations across IHE Document Sharing Communities”, in 24th European Medical Informatics Conference (MIE 2012), Pisa, Italy, 2012.
  • L. Bastião Silva, C. Costa, and J. L. Oliveira, “A DICOM relay service supported on cloud resources”, in 5th International Conference on Health Informatics (HEALTHINF 2012), Vilamoura, Portugal, 2012.
  • T. Pedrosa, R. P. Lopes, J. C. Santos, C. Costa, and J. L. Oliveira, “A secury personal health record repository”, in 5th International Conference on Health Informatics (HEALTHINF 2012), Vilamoura, Portugal, 2012.
  • L. Velte, T. Pedrosa, C. Costa, and J. L. Oliveira, “An OPENEHR repository based on a native XML database”, in 5th International Conference on Health Informatics (HEALTHINF 2012), Vilamoura, Portugal, 2012.
  • R. Mendonça, P. Lopes, H. Rocha, J. Oliveira, L. Vilarinho, R. Santos, and J. L. Oliveira, “Gathering and managing genotype and phenotype information about rare diseases patients”, in 5th International Conference on Health Informatics (HEALTHINF 2012), Vilamoura, Portugal, 2012.
  • J. Melo, J. Arrais, P. Lopes, N. Rosa, M. J. Correia, M. Barros, and J. L. Oliveira, “OralCard – web information system for oral health”, in 5th International Conference on Health Informatics (HEALTHINF 2012), Vilamoura, Portugal, 2012.
  • C. Viana-Ferreira, C. Costa, and J. L. Oliveira, “Dicoogle Relay – a Cloud Communications Bridge for Medical Imaging”, in 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2012), Rome, Italy, 2012.
  • R. Mendonça, A. F. Rosa, J. L. Oliveira, and A. Teixeira, “Towards ontology based health information search in Portuguese – A case study in neurologic diseases”, in 7th Iberian Conference on Information Systems and Technologies (CISTI 2012), Madrid, Spain, 2012.
  • P. Gaspar, J. Carbonell, and J. L. Oliveira, “Parameter influence in genetic algorithm optimization of support vector machines”, in 7th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2012), Salamanca, Spain, 2012.
  • P. Lopes, R. Mendonça, H. Rocha, J. Oliveira, L. Vilarinho, R. Santos, and J. L. Oliveira, “A Rare Disease Patient Manager”, in 7th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2012), Salamanca, Spain, 2012.
  • P. Lopes and J. L. Oliveira, “COEUS: A Semantic Web Application Framework”, in Semantic Web Applications and Tools for Life Sciences (SWAT4LS 2011), London, UK, 2011, pp. 87-90.
  • S. Matos and J. L. Oliveira, “Prioritizing Literature Search Results Using a Training Set of Classified Documents”, in 5th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2011), vol. 93, pp. 381-388, 2011.
  • P. Lopes and J. L. Oliveira, “Towards Knowledge Federation in Biomedical Applications”, in Proceedings of the 7th International Conference on Semantic Systems (I-Semantics 2011), Graz, Austria, 2011, pp. 729-734.
  • P. Lopes and J. L. Oliveira, “A Semantic Web Application Framework for Health Systems Interoperability”, in Proceedings of the first international workshop on Managing interoperability and complexity in health systems (MIXHS’11), Graz, Austria, 2011.
  • C. Santos, T. Pedros, C. Costa, and J. L. Oliveira, “On the Use of Openehr in a Portable Phr”, Healthinf 2011: Proceedings of the International Conference on Health Informatics (Healthinf 2011), pp. 351-356, 2011.
  • T. Pedrosa, R. P. Lopes, J. C. Santos, C. Costa, and J. L. Oliveira, “Hybrid Electronic Health Records”, Healthinf 2011: Proceedings of the International Conference on Health Informatics (Healthinf 2011), pp. 571-574, 2011.
  • D. Campos, D. Rebholz-Schuhmann, S. Matos, and J. L. Oliveira, “A CRF-based approach to harmonize heterogeneous gene/protein annotations”, in Second CALBC Workshop, Hinxton, UK, 2011.
  • L. Bastião, C. Costa, A. Silva, and J. L. Oliveira, “A PACS Gateway to the Cloud”, in 6th Iberian Conference on Information Systems and Technologies (CISTI 2011), Chaves, Portugal, 2011, pp. 519-524.
  • J. Arrais and J. L. Oliveira, “Gene-disease prioritization through biomedical networks,” in 10th IEEE International Conference on Information Technology and Applications in Biomedicine (ITAB 2010), Corfu, Greece, 2010.
  • P. Lopes, D. Campos, and J. L. Oliveira, “A tagging system for bioinformatics resources,” in 10th IEEE International Conference on Information Technology and Applications in Biomedicine (ITAB 2010), Corfu, Greece, 2010.
  • J. Arrais and J. L. Oliveira, “On the exploitation of cloud computing in Bioinformatics,” in 10th IEEE International Conference on Information Technology and Applications in Biomedicine (ITAB 2010), Corfu, Greece, 2010.
  • P. Lopes and J. L. Oliveira, “An extensible platform for variome data integration,” in 10th IEEE International Conference on Information Technology and Applications in Biomedicine (ITAB 2010), Corfu, Greece, 2010.
  • L. S. Ribeiro, C. Costa, and J. L. Oliveira, “A Distributed and Reliable DICOM Storage Facility,” in 28th International EuroPACS Meeting (CARS 2010), Geneva, Switzerland, 2010.
  • F. Martin-Sanchez, V. Lopez-Alonso, L. Salamanca, J. L. Oliveira, and E. Andres, “Managing Knowledge Related to the Clinical Relevance of Biomarkers: An Example in Parkinson’s Disease”, in 2010 AMIA Summit on Translational Bioinformatics, San Francisco, CA, USA, 2010.
  • S. Matos, J. Arrais, and J. L. Oliveira, “Expanding Gene-based PubMed Queries”, in 4th International Workshop on Practical Applications of Computational Biology and Bioinformatics (IWPACBB 2010), Guimarães, Portugal, 2010.
  • J. Arrais, J. Pereira, P. Lopes, S. Matos, and J. L. Oliveira, “Improving cross mapping in biomedical databases”, in 4th International Workshop on Practical Applications of Computational Biology and Bioinformatics (IWPACBB 2010), Guimarães, Portugal, 2010.
  • J. P. Lousado, J. L. Oliveira, G. Moura, and M. A. S. Santos, “An application for study tandem repeats in ortologous genes”, in 4th International Workshop on Practical Applications of Computational Biology and Bioinformatics (IWPACBB 2010), Guimarães, Portugal, 2010.
  • P. Lopes and J. L. Oliveira, “A Holistic Approach for Integrating Genomic Variation Information,” in Xth Spanish Symposium on Bioinformatics (JBI2010), Malaga, Spain, 2010.
  • J. P. Lousado, J. L. Oliveira, G. Moura, and M. A. S. Santos, “Análise da evolução de repetições de codões e de aminoácidos em dados biológicos,” in 5th Iberian Conference on Information Systems and Technologies (CISTI 2010), Santiago de Compostela, Spain, 2010.
  • D. Campos, S. Matos, and J. L. Oliveira, “Recognition of gene/protein names using Conditional Random Fields,” in International Joint Conference on Knowledge Discovery and Information Retrieval (KDIR 2010), Valencia, Spain, 2010.
  • L. S. Ribeiro, L. Bastião, C. Costa, and J. L. Oliveira, “Email-P2P Gateway to Distributed Medical Imaging Repositories”, in HEALTHINF 2010, Valencia, Spain, 2010.
  • J. C. Santos, T. Pedrosa, C. Costa, and J. L. Oliveira, “Modelling a Portable Personal Health Record”, in HEALTHINF 2010, Valencia, Spain, 2010.
  • T. Pedrosa, R. P. Lopes, J. C. Santos, C. Costa, and J. L. Oliveira, “Towards an EHR architecture for mobilde citizens”, in HEALTHINF 2010, Valencia, Spain, 2010.
  • J. C. Santos, T. Pedrosa, C. Ferreira, C. Costa, and J. L. Oliveira, “Gathering and Managing Complementary Diagnostic Tests,” in 5th Iberian Conference on Information Systems and Technologies (CISTI 2010), Santiago de Compostela, Spain, 2010.
  • L. S. Ribeiro, C. Costa, and J. L. Oliveira, “A Proxy of DICOM services”, in SPIE Medical Imaging 2010, S. Diego, CA, USA, 2010.
  • J. Arrais, J. Pereira, J. Fernandes, and J. L. Oliveira, “GeNS: A Biological Data Integration Platform”, in World Academy of Science, Engineering and Technology (WASET 2009), Venice, Italy, 2009, pp. 416 – 421.
  • P. Lopes and J. L. Oliveira, “Cloud Computing and Digital Libraries : First Perspectives on a Future Technological Alliance “, in 9ª Conferência da Associação Portuguesa de Sistemas de Informação (CAPSI 2009), Viseu, Portugal, 2009.
  • M. Pinheiro, M. J. Simões, C. Egas, and J. L. Oliveira, “Identifying SNPs candidates using 454 sequencing technology”, in Jornadas de Bioinformática (JB 2009), Lisbon, Portugal, 2009.
  • P. Lopes, J. Arrais, and J. L. Oliveira, “Link Integrator: A Link-based Data Integration Architecture”, in International Conference on Knowledge Discovery and Information Retrieval (KDIR 2009), Madeira, Portugal, 2009.
  • P. Lopes, D. Pinto, D. Campos, and J. L. Oliveira, “Arabella: A Directed Web Crawler”, in International Conference on Knowledge Discovery and Information Retrieval (KDIR 2009), Madeira, Portugal, 2009.
  • T. Pedrosa, C. Costa, R. P. Lopes, and J. L. Oliveira, “Virtual Health Card System”, in Inforum 2009, Lisbon, Portugal, 2009.
  • D. Polónia, C. Costa, J. L. Oliveira, and A. M. O. Duarte, “Inequality problems in the distribution of radiologists in Portugal: Requirements for the creation of an imaging marketplace”, in eChallenges 2009, Ankara, Turkey, 2009.
  • P. Lopes, J. Arrais, and J. L. Oliveira, “A Client-side Workflow Management System”, in 3rd International Workshop on Practical Applications of Computational Biology and Bioinformatics (IWPACBB 2009), 2009.
  • J. P. Lousado, G. Moura, M. A. S. Santos, and J. L. Oliveira, “Analysing the evolution of repetitive strands in genomes”, in 3rd International Workshop on Practical Applications of Computational Biology and Bioinformatics (IWPACBB 2009), 2009.
  • S. Matos, A. Barreiro, J.L. Oliveira, “Syntactic Parsing for Bio-Molecular Event Detection from Scientific Literature”, 14th Portuguese Conference on Artificial Intelligence, EPIA’2009, Aveiro, Oct. 2009.
  • P. Lopes, J. Arrais and J. L. Oliveira, “Dynamic Service Integration using Web-based Workflows” in 10th International Conference on Information Integration and Web Applications & Services“, OCG – ACM, Linz, AT, Nov. 2008, pp. 622-625
  • D. Santos, C. Costa, J. L. Oliveira, and A. Neves, “Alternative lossless compression algorithms in X-ray cardiac images” in Computational Vision and Medical Image Processing, N. J. João Tavares, Ed. London: Taylor & Francis Group, 2008, pp. 143-146.
  • D. Polónia, C. Costa, and J. L. Oliveira, “A Model to Optimize the Use of Imaging Equipment and Human Skills Scattered in Very Large Geographical Areas”, in 9th International Conference on Enterprise Information Systems (ICEIS’2004), Madeira, Portugal, 2007.
  • V. Afreixo, A. Freitas, M. Pinheiro, J. L. Oliveira, G. Moura, and M. A. S. Santos, “Exploiting a Biclustering algorithm in ORFeome analysis”, in Proceedings of the 2007 VLDB Workshop on Data Mining in Bioinformatics, Vienna, Austria, 2007.
  • A. Freitas, J. Duarte, M. Pinheiro, J. L. Oliveira, G. Moura, and M. A. S. Santos, “Homo sapiens versus Pan troglodytes: quão diferentes são?” in Actas do XIV Congresso Nacional da Sociedade Portuguesa de Estatística, Covilhã, Portugal, 2007.
  • J. Duarte, A. Freitas, M. Pinheiro, J. L. Oliveira, G. Moura, and M. A. S. Santos, “ISA: um algoritmo de bi-classificação?” in Actas do XIV Congresso Nacional da Sociedade Portuguesa de Estatística, Covilhã, Portugal, 2007.
  • A. Freitas, M. Pinheiro, V. Afreixo, J. Duarte, J. L. Oliveira, G. Moura, and M. A. Santos, “A median-based Iterative Signature Algorithm”, in IASC 07 – Statistics for Data Mining, Learning and Knowledge Extraction, Aveiro, Portugal, 2007.
  • A. Freitas, M. Pinheiro, J. L. Oliveira, G. Moura, and M. A. Santos, ” A new limiting distribution for a statistical test for the homogeneity of two multinomial populations”, in Workshop in Statistic on Genomics and Proteomic, CIM, 2006.
  • J. Arrais, D. Polónia, and J. L. Oliveira, “A prospective study on the integration of microarrays data in HIS/ERP”, in Biological and Medical Data Analysis (ISBMDA’ 2006), Lecture Notes in Computer Science – Volume 4345, Thessaloniki, Greece, 2006.
  • D. Polónia, C. Costa, and J. L. Oliveira, “Optimizing PACS and imaging resources”, in The XX International Congress of the European Federation for Medical Informatics (MIE’2006), Maastricht, Netherlands, 2006.
  • G. Dias, J. L. Oliveira, F. Vicente, and F. Martín-Sanchez, “Integrating Medical and Genomic Data: a Sucessful Example for Rare Diseases”, in The XX International Congress of the European Federation for Medical Informatics (MIE’2006), Maastricht, Netherlands, 2006.
  • J. Arrais, J. L. Oliveira, G. Grimes, S. Moodie, K. Robertson, and P. Ghazal, “Microarray data sharing in BioMedicine”, in The XX International Congress of the European Federation for Medical Informatics (MIE’2006), Maastricht, Netherlands, 2006.
  • D. Polónia, C. Costa, and J. L. Oliveira, “A PACS based GRID of resources”, in 4th International EuroPACS Conference (EuroPACS 2006), Trondheim, Norway, 2006.
  • G. Dias, J. L. Oliveira, F. Vicente, and F. Martin-Sanchez, “Integration of Genetic and Medical Information Through a Web Crawler System”, in Biological and Medical Data Analysis (ISBMDA’ 2005), Lecture Notes in Computer Science – Volume 3745, Aveiro, Portugal, 2005.
  • C. Costa, J. L. Oliveira, A. Silva, V. Ribeiro, and J. Ribeiro, “Data Management and Visualization Issues in a Fully Digital Echocardiography Laboratory”, in Biological and Medical Data Analysis (ISBMDA’ 2005), Lecture Notes in Computer Science – Volume 3745, Aveiro, Portugal, 2005.
  • C. Costa, J. L. Oliveira, A. Silva, V. Ribeiro, and J. Ribeiro, “A Telemedicine Platform for Cardiovascular Ultrasound”, in The XIX International Congress of the European Federation for Medical Informatics (MIE’2005), Geneve, Switzerland, 2005.
  • D. Polónia, C. Costa, and J. L. Oliveira, “Architecture evaluation for the implementation of a Regional Integrated Electronic Health Record”, in The XIX International Congress of the European Federation for Medical Informatics (MIE’2005), Geneve, Switzerland, 2005.
  • M. Pinheiro, J. L. Oliveira, M. A. S. Santos, H. Rocha, M. L. Cardoso, and L. Vilarinho, “Results of a Biomedical Application in Newborn Screening Programs”, in The 3rd European Medical and Biological Engineering Conference (EMBEC’05), Prague, Czech Republic, 2005.
  • J. Arrais, L. Silva, M. Rodrigues, L. Carreto, J. L. Oliveira, and M. A. S. Santos, “Why Another Microarrays LIMS”, in The 3rd European Medical and Biological Engineering Conference (EMBEC’05), Prague, Czech Republic, 2005.
  • D. Polónia, J. L. Oliveira, and N. P. Rocha, “Overview of information systems training in Portuguese medicine courses”, in Health and Medical Informatics Applications – Educational Aspects (EFMI-STC 2005), Athens, Greece, 2005.
  • D. Polónia and J. L. Oliveira, “Health Information Systems and Telematics: A best of breed evaluation framework for the Portuguese case”, in European Health Management Association Annual Conference 2005 (EHMA’2005), Barcelona, Spain, 2005.
  • M. Pinheiro, J. L. Oliveira, M. A. S. Santos, H. Rocha, M. L. Cardoso, and L. Vilarinho, “NeoScreen: A software application for MS/MS newborn screening analysis”, in Biological and Medical Data Analysis (ISBMDA’2004), Lecture Notes in Computer Science – Volume 3337, Barcelona, Spain, 2004.
  • F. Vicente, I. Hermosilla, M. García-Remesal, D. Pérez del Rey, B. Romero, I. Oliveira, J. L. Oliveira, A. S. Pereira, and F. Martin-Sanchez, “Infogenmed: Un Laboratorio Virtual para la Integración de Información Clínica y Genética en Aplicaciones Médicas”, in VII Congreso Nacional de Informático de la Salud (Inforsalud’2004), Madrid, Spain, 2004.
  • Oliveira, J. L. Oliveira, F. Martin-Sanchez, V. Maojo, and A. S. Pereira, “Biomedical information integration for health applications with Grid: a requirements perspective”, in Healthgrid 2004, Clermont-Ferrand, France, 2004.
  • D. Polónia, J. L. Oliveira, and M. O. Duarte, “Information Systems (IS) in the Third and Fourth Generation Mobile Operator”, in 5ª Conferência da Associação Portuguesa de Sistemas de Informação (CAPSI’2004), Lisbon, 2004.
  • C. Costa, A. Silva, J. L. Oliveira, V. Ribeiro, and J. Ribeiro, “Himage PACS: A new approach to storage, integration and distribution of cardiologic images” in Progress in Biomedical Optics and Imaging, vol. 5, H. H. Ratib OM, Ed., SPIE, 2004, pp. 277-287.
  • J. L. Oliveira, G. Dias, I. Oliveira, P. Rocha, I. Hermosilla, F. Vicente, I. Spiteri, F. Martin-Sanchez, and A. S. Pereira, “DiseaseCard: a web-based tool for the collaborative integration of genetic and medical information”, in Biological and Medical Data Analysis (ISBMDA’2004), Lecture Notes in Computer Science – Volume 3337, Barcelona, Spain, 2004.
  • D. Polónia, I. Oliveira, and J. L. Oliveira, “A Business Process Model for Public Health Information Systems: A Governmental Perspective”, in 6th International Conference on Enterprise Information Systems (ICEIS’2004), Porto, Portugal, 2004.
  • C. Costa, J. L. Oliveira, and A. Silva, “E-Services in Mission-Critical Organizations: Identification Enforcement”, in 6th International Conference on Enterprise Information Systems (ICEIS’2004), Porto, Portugal, 2004.
  • M. García-Remesal, V. Maojo, H. Billhardt, J. Crespo, R. Alonso-Calvo, D. Pérez, F. Martín, V. López, J. Sánchez, F. Vicente, M. García-Rojo, A. Gómez de la Cámara, A. Sousa, J. L. Oliveira, I. Oliveira, M. Santos, and A. Babic, “Designing New Methodologies for Integrating Biomedical Information in Clinical Trials”, in EuroMISE 2004, Prague, Czech Republic, 2004.
  • C. Costa, A. Silva, J. L. Oliveira, A. S. Pereira, and V. Ribeiro, “A New Concept for an Integrated Healthcare Access Model”, in Medical Informatics Europe (MIE’2003), Saint Malo, France, 2003.
  • C. Costa, J. L. Oliveira, and A. Silva, “Authentication Model to Enforce Network Entities Identification”, in 4rd Conference on Telecommunications (ConfTele’2003), Aveiro, Portugal, 2003.
  • C. Costa, J. L. Oliveira, A. Silva, and V. Gama, “An Integrated Access Interface to Multimedia EPR”, in 21st International EuroPACS Meeting (EuroPACS’2003), London, United Kingdom, 2003.
  • Oliveira, J. L. Oliveira, M. Santos, F. Martin-Sanchez, and A. S. Pereira, “On the requirements of biomedical information tools for health applications: the INFOGENMED case study”, in 7th Portuguese Conference on Biomedical Engineering (BioEng’2003), Lisbon, Portugal, 2003.
  • C. Costa, J. L. Oliveira, and A. Silva, “Electronic Patient Record Virtually Unique based on a Crypto Smart Card”, in International Conference on Web Engineering (ICWE’2003), Lecture Notes in Computer Science – Volume 2722 / 2003, Oviedo, Spain, 2003.
  • C. Costa, J. L. Oliveira, and A. Silva, “Critical Information Systems Authentication based on PKC and Biometrics”, in International Conference on Web Engineering (ICWE’2003), Lecture Notes in Computer Science – Volume 2722 / 2003, Oviedo, Spain, 2003.
  • C. Costa, J. L. Oliveira, and A. Silva, “A User-Oriented Model to Manage Multiple Digital Credentials”, in IEEE 5th International Conference on Enterprise Information Systems (ICEIS’2003), Angers, France, 2003.
  • J. C. Santos, J. L. Oliveira, and C. Costa, “A User-oriented Multi-service Access Control System”, in 5ª Conferência sobre Redes de Computadores (CRC’2002), Faro, Portugal, 2002.
  • C. Costa, J. L. Oliveira, and A. Silva, “A Trusted Brokering Service for PKI Interoperability and Thin-Clients Integration”, in IEEE Third International Conference on Enterprise Information Systems (ICEIS’2001), Setúbal, Portugal, 2001.
  • C. Costa, J. L. Oliveira, and A. Silva, “Um Novo Mecanismo de Autenticação para Sistemas de Informação Clínica” (in portuguese), in 4ª Conferência sobre Redes de Computadores (CRC’2001), Covilhã, Portugal, 2001.
Abstracts
  • P. M. Coloma, M. J. Schuemie, G. Trifirò, L. Furlong, E. V. Mulligen, A. Bauer-Mehren, P. Avillach, J. Kors, F. Sanz, J. Mestres, J. L. Oliveira, S. Boyer, E. A. Helgee, M. Molokhia, J. Matthews, D. Prieto-Merino, R. Gini, R. M. C. Herings, G. Mazzaglia, G. Picelli, L. Scotti, L. Pedersen, J. V. d. Lei, and M. C. J. M. Sturkenboom, “Triage and Evaluation of Potential Safety Signals Identified from Electronic Healthcare Record Databases,” in 12th Annual Meeting of the International Society of Pharmacovigilance (ISoP 2012), Cancun, Mexico, 2012.
  • P. Lopes and J. L. Oliveira, “COEUS: “Semantic Web in a box” for biomedical applications,” in 11th European Conference on Computational Biology (ECCB 2012), Basel, Switzerland, 2012.
  • P. Lopes, D. Campos, T. Nunes, and J. L. Oliveira, “Delivering advanced pharmacovigilance with the EU-ADR Web Platform,” in 11th European Conference on Computational Biology (ECCB 2012), Basel, Switzerland, 2012.
  • M. J. Correira, N. Rosa, I. Silveira, J. Arrais, J. L. Oliveira, and M. Barros, “Oral microbial proteome: clues of OralCard”, in 22nd IUBMB & 37th FEBS Congress, Seville, Spain, 2012.
  • N. Rosa, J. Arrais, J. Melo, E. Coelho, M. J. Correira, J. L. Oliveira, and M. Barros, “OralCard: a bioinformatic tool dedicated to the oral cavity system”, in 22nd IUBMB & 37th FEBS Congress, Seville, Spain, 2012.
  • E. Molero, C. Diaz, F. Sanz, J. L. Oliveira, G. Trifirò, A. Fourrier, M. Molokhia, L. Pedersen, S. Boyer, L. Scotti, R. Gini, R. Herings, C. Giaquinto, M. I. Loza, G. Mazzaglia, J. v. d. Lei, and M. Sturkenboom, “The EU-ADR Alliance: A Federated Collabora- tive Framework for Drug Safety Studies,” in 12th Annual Meeting of the International Society of Pharmacovigilance (ISoP 2012), Barcelona, Spain, 2012.
  • P. Lopes, J. Arrais, and J. L. Oliveira, “A Knowledge Interoperability Framework for Integrating Genotype-to-Phenotype Data”, in III Xornadas Galegas de Bioinformatics (XGB 2012), Vigo, Spain, 2011.
  • D. Campos, S. Matos, and J. L. Oliveira, “A machine learning-based tool for biomedical entity recognition (Best Poster)”, in III Xornadas Galegas de Bioinformatics (XGB 2012), Vigo, Spain, 2011.
  • J. Arrais and J. L. Oliveira, “Using biomedical networks to gene-disease indentification”, in III Xornadas Galegas de Bioinformatics (XGB 2012), Vigo, Spain, 2011.
  • P. Lopes and J. L. Oliveira, “An Integrated View for Human Variome Information,” in 14th International Conference on Research in Computational Molecular Biology (RECOMB 2010), Lisbon, Portugal, 2010.
  • P. Gaspar, J. L. Oliveira, J. Frommlet, G. Moura, and M. A. S. Santos, “A gene multi-optimization tool as novel approach to heterologous expression,” in 14th International Conference on Research in Computational Molecular Biology (RECOMB 2010), Lisbon, Portugal, 2010.
  • J. Frommet, P. Gaspar, M. Pinheiro, J. L. Oliveira, A. C. Gomes, G. Moura, and M. A. S. Santos, “Integrating tRNA abundance, codon-usage, codon-context and functional rare codon data in de novo synthesis of Plasmodium falciparum genes for optimal expression in Escherichia coli,” in 23rd tRNA Workshop (tRNA 2010), Aveiro, Portugal, 2010.
  • S. Matos, J. Arrais, J. Maia-Rodrigues, and J. L. Oliveira, “QuExT: a concept-based query expansion approach for literature retrieval from MEDLINE”, in Jornadas de Bioinformática (JB 2009), Lisbon, Portugal, 2009.
  • P. Lopes and J. L. Oliveira, “Integration of Variome Data Through a Link Discovery Strategy”, in Jornadas de Bioinformática (JB 2009), Lisbon, Portugal, 2009.
  • A. Freitas, V. Afreixo, M. Pinheiro, J. L. Oliveira, and M. A. S. Santos, “Uma avaliação da performance do algoritmo de bi-classificação ISA-mediana”, in XVI Jornadas de Classificação e Análise de Dados (JOCLAD 2009), Faro, Portugal, 2009.
  • S. Matos, A. Barreiro, “Syntactic-semantic analysis for information extraction in biomedicine”, NooJ Conference 2009, Jozeur, Tunisia, Jun 2009.
  • Maria dos Santos, Miguel Pinheiro, Manuel A. S. Santos (2008). Candida albicans as a model system to study genetic code alterations at genome level. 9th ASM Conference on Candida and Candidiasis, Jersey City, USA (Mar 24-28)
  • M. Santos, M. Pinheiro, J. L. Oliveira and M. A. S. Santos, “Comparative tRNomics of a genetic code alteration”, ESF-EMBO Symposium on Comparative Genomics of Eukaryotic Microorganisms: Eukaryotic Genome Evolution, Sant Feliu de Guixols, Spain, 2007.
  • M. Pinheiro, G. Moura, A. Freitas, M. A. S. Santos, and J. L. Oliveira, “A bioinformatics system to analyze sequences at a genomic scale”, in XVth National Congress of Biochemistry (NBC 2006) Aveiro, Portugal, 2006.
  • G. Moura, M. Pinheiro, C. Gomes, A. Freitas, J. L. Oliveira, and M. A. S. Santos, “Large Scale Comparative Codon Context Analysis Unveils Novel Rules Governing Gene Evolution”, in XVth National Congress of Biochemistry (NBC 2006) Aveiro, Portugal, 2006.
  • J. P. Lousado, G. Moura, M. Pinheiro, J. L. Oliveira, and M. A. S. Santos, “Large Scale Comparative Genomics of Codon Context”, in XVth National Congress of Biochemistry (NBC 2006) Aveiro, Portugal, 2006.
  • S. Lima, E. Fonseca, J. L. Oliveira, and C. Egas, “Computational Methodologies for Metagenomics Projects”, in XVth National Congress of Biochemistry (NBC 2006) Aveiro, Portugal, 2006.
  • C. Gomes, G. Moura, A. C. Gomes, J. L. Oliveira, M. Pinheiro, A. Freitas, and M. A. S. Santos, “The role of codon context on mRNA decoding error in vivo in yeast”, in XVth National Congress of Biochemistry (NBC 2006) Aveiro, Portugal, 2006.
  • A. Freitas, L. Ferreira, J. Duarte, M. Pinheiro, J. L. Oliveira, G. Moura, and M. A. S. Santos, “Homo Sapiens Vs Pan Troglodytes: How Diferent Are They?” in XVth National Congress of Biochemistry (NBC 2006) Aveiro, Portugal, 2006.
  • C. Egas, J. L. Oliveira, M. A. S. Santos, M. S. Costa, and C. Faro, “Whole Genome shotgun mapping of Rubrobacter radiotolerans”, in XVth National Congress of Biochemistry (NBC 2006) (Invited talk), Aveiro, Portugal, 2006.
  • L. Carreto, P. Pereira, J. Arrais, J. L. Oliveira, and M. A. S. Santos, “National Facility For DNA Microarrays”, in XVth National Congress of Biochemistry (NBC 2006) (Invited talk), Aveiro, Portugal, 2006.
  • J. Arrais, J. L. Oliveira, G. Campos, L. Carreto, and M. A. S. Santos, “Microarray data: from the hybridisation to the analysis”, in European Summer School in Biomedical Informatics, Balatonfüred, Hungary, 2006.
  • J. Arrais, L. Carreto, M. A. S. Santos, and J. L. Oliveira, “Collaborative work on microarrays using MAGE-ML”, in 9th International Meeting of the Microarray Gene Expression Data Society (MGED9), Seattle, Washington, USA, 2006.
  • J. Arrais, L. Carreto, H. Pais, F. Lopes, M. A. S. Santos, and J. L. Oliveira, “A Laboratory Information Management System for Microarray Data Storage, Sharing and Analysis”, in XVth National Congress of Biochemistry (NBC 2006) Aveiro, Portugal, 2006.
  • P. R. Almeida, L. Carreto, J. L. Oliveira, and M. A. S. Santos, “Software-Assisted Design of Probes for SNPs Detection using Oligonucleotide Microarrays: Applications in a Case Study”, in XVth National Congress of Biochemistry (NBC 2006) Aveiro, Portugal, 2006.
  • J. Arrais, J. L. Oliveira, G. Campos, L. Carreto, and M. A. S. Santos, “Microarray data: from the hybridisation to the analysis”, in European Summer School in Biomedical Informatics, Balatonfüred, Hungary, 2006.
  • J. Arrais, L. Carreto, M. A. S. Santos, and J. L. Oliveira, “Collaborative work on microarrays using MAGE-ML”, in 9th International Meeting of the Microarray Gene Expression Data Society (MGED9), Seattle, Washington, USA, 2006.
  • L. Carreto, M. C. Santos, J. Arrais, M. Rodrigues, L. Silva, J. L. Oliveira, and M. A. S. Santos, “Implementation of a National Facility for DNA Microarrays in Portugal”, in 8th International Meeting of the Microarray Gene Expression Data Society (MGED8), Bergen, Norway, 2005.
  • J. L. Oliveira, M. Pinheiro, M. A. S. Santos, H. Rocha, M. L. Cardoso, and L. Vilarinho, “On the Processing of MS/MS Data: an Application for Metabolic Diseases Screening”, in XIV Congresso Nacional de Bioquímica, Vilamoura, Portugal, 2004.
  • M. Pinheiro, V. Afreixo, G. Moura, A. Freitas, M. A. S. Santos, and J. L. Oliveira, “Bioinformation System for Unveil General Rules of Codon Context”, in XIV Congresso Nacional de Bioquímica, Vilamoura, Portugal, 2004.
  • G. Moura, M. Pinheiro, V. Afreixo, A. Freitas, J. L. Oliveira, and M. A. S. Santos, “Comparative codon context analysis in complete genomes unveils new decoding rules in yeast”, in XIV Congresso Nacional de Bioquímica, Vilamoura, Portugal, 2004.
  • G. Moura, M. Pinheiro, V. Afreixo, A. Valente, J. L. Oliveira, and M. A. S. Santos, “Comparative codon context analysis at a genomic scale defines new mRNA decoding rules”, in Translational Control Meeting, Cold Spring Harbor, New York, 2004.
  • L. Carreto, J. Pereira, J. L. Oliveira, A. S. Pereira, V. Afreixo, A. Valente, and M. A. S. Santos, “Implementation of a DNA-microarray platform for yeast expression, genome diversity and evolution and molecular diagnostics research.” in XII Jornadas de Biologia de Leveduras (Leveduras’2004), Aveiro, Portugal, 2004.
  • G. Moura, M. Pinheiro, V. Afreixo, A. Valente, J. L. Oliveira, and M. A. S. Santos, “Genome scale codon context analysis for Saccharomyces cerevisiae and Candida albicans.” in XII Jornadas de Biologia de Leveduras (Leveduras’2004), Aveiro, Portugal, 2004.
  • M. Pinheiro, V. Afreixo, G. Moura, G. Dias, A. S. Pereira, A. Valente, M. A. S. Santos, and J. L. Oliveira, “Bioinformation system and statistical methodologies for gene primary structure analysis”, in EuroMISE 2004, Prague, Czech Republic, 2004.
  • J. L. Oliveira, M. Pinheiro, G. Dias, G. Moura, V. Afreixo, A. Valente, A. S. Pereira, and M. A. S. Santos, “New software tools for gene analysis”, in ESF Programme in Functional Genomics: 1st European Conference (ESFFG’2003), Prague, Czech Republic, 2003.
  • Oliveira, A. Furtado, J. L. Oliveira, A. S. Pereira, V. Maojo, F. Martin-Sanchez, A. Babic, and M. Santos, “Integration of Genetic and Clinical Information Sources for Health Applications”, in ESF Programme in Functional Genomics: 1st European Conference (ESFFG’2003), Prague, Czech Republic, 2003.
  • J. L. Oliveira, G. Dias, R. Silva, and M. A. S. Santos, “An open environment for management of proteomics data and projects”, in ESF Programme in Functional Genomics: 1st European Conference (ESFFG’2003), Prague, Czech Republic, 2003.
Thesis
  • Pedro Lopes
    Title: Service Composition in Biomedical Applications
    Supervisor: José Luis Oliveira
    Date: 2012
  • Nuno Rosa
    Title: From the oral cavity proteome to the proteome
    Supervisor: Marlene Barros, José Luis Oliveira
    Date: 2012
  • Daniel Ferreira Polónia
    Title: An electronic market for teleradiology services
    Supervisor: José Luis Oliveira, Manuel Oliveira Duarte
    Date: 2011
  • José Paulo Lousado
    Title: Analysis of tandem repeats in DNA primary structures
    Supervisor: José Luis Oliveira
    Date: 2011
  • Miguel Monsanto Pinheiro
    Title: Computational systems for the study of the primary structure and redesign of genes
    Supervisor: José Luis Oliveira, Manuel Santos
    Date: 2010
  • Joel Perdiz Arrais
    Title: Microarrays information systems and healthcare information systems
    Supervisor: José Luis Oliveira
    Date: 2010
  • Carlos Manuel Azevedo Costa
    Title: A security dynamic model for healthcare information systems
    Supervisor: José Luis Oliveira, Augusto Silva
    Date: 2004
Developing new Bioinformatics tools for genome analysis

Funding entity: POCTI-32030/2001
Period: 2002-2005

Biologists have been wondering for many years how organisms evolved highly accurate information maintenance, transfer and decoding machineries. In particular, how the astonishing translational decoding rate of 20 codons per second is achieved with an average error of 10-4 to 10-5 per codon decoded, and how does the ribosome maintain the reading frame. The tools to answer these questions are not yet available but the row DNA sequencing data is. To shed new light into this important question, we have developed a software package that simulates ribosome scanning and reading during mRNA translation. The software screens fully or partially sequenced genomes and determines the arrangement of any particular codon in relation to the others by simultaneously fixing P-site codons and “memorizing” E and A-site codons during each translocation cycle. In doing so, it builds a genome wide codon context map that allows for identification of potential error prone mRNA sequences and gene expression regulatory points.

In this project, the various tools already developed will be integrated into a single software package to allow for automated search, downloading and editing of row DNA sequence data. Software tools for data display and new mathematical methodologies for identification of general rules governing mRNA translation will be developed. New tools for mapping mRNA regions of high decoding error and putative gene expression regulatory sequences present in the mRNAs, will also be developed. Finally, a database and an Internet Home Page will be built for making the data available to the scientific community. These in silico studies will be complemented with in vivo experiments. For this, a multidisciplinary team including two computing engineers, two mathematicians, one physicist, one biochemist and one molecular biologist has been assembled. To our knowledge this is the first Portuguese multidisciplinary team set up for functional genomics and the only one actively engaged on the development of software tools and mathematical models for genome analysis. It is expected that this project will provide important new insight on the role of the translational machinery on genome evolution.

Functional Proteomics in Candida albicans: Developing an Integrated Database for the Management of Proteomics projects

Funding entity: POCTI-32942/99
Period: 2001-2004

Candida albicans is an important human pathogen which exists as a commensal in at least 50% of the human population. It accounts for more than 60% of all fungal infections and is now the fourth most common form of septicaemia in Western hospitals with an associated mobidity between 30 and 50%. It is also a major cause for concern in HIV-infected populations where 84% of the patients develop oropharyngeal C.albicans colonisation and 55% develop clinical thrush. C. albicans pathogenesis is dependent upon a wide range of virulence factors, namely a myriad of morphogenesis associated factors, represents a major challenge to the elucidation of C. albicans pathogenesis at the molecular level through classic molecular and biochemical methodologies. The diploid nature of C. albicans, its alternative genetic code and its recalcitrance to genetic analysis, add extra difficulties to its study and to the development of new antifungals. However, the advent of new genetics and molecular technologies which allow for genome wide analysis is promising to alter the present situation.

This project aims at integrating classical genetics and biochemical approaches with newly developed, proteomics and bioinformatics methodologies to uncover new virulence factors associated to morphogenesis.

Software tools are been developed for management of biological data extracted from protein 2D-maps, for helping planning and following up experimental protocols and for data storing. Additionally, mathematical algorithms are also been developed for creating theoretical protein 2D-maps for comparative proteomics studies.

Query term expansion methodologies for improved biomedical literature retrieval

Funding entity: FCT PTDC/EIA-CCO/100541/2008
Period: 2010-2013

The objective of this project is to develop a query expansion and document ranking method specially aimed at obtaining, from the MEDLINE database, a ranked list of publications that are most significant to a set of genes.

Faculty and Postdocs
  • José Luís Oliveira
  • Carlos Costa
  • Sérgio Matos
  • Joel Arrais
  • Pedro Lopes
  • Susana Brás
  • Raquel Silva
  • Luísa Guedes
  • Armando Pinho
  • Raquel Sebastião
  • Paula Alexandra Silva
Post-docs
  • Sérgio Matos
  • Joel Arrais
PhD Students
  • João Cândido
  • Frederico Valente
  • Paulo Gaspar
  • Carlos Ferreira
  • Luis Bastião
  • Fernanda Barbosa
  • Eriksson Monteiro
  • Edgar Coelho
  • Diogo Pratas
  • Tiago Godinho
  • Pedro Sernadela
Researchers
  • Andreia Davide
  • Fábio Falcão
  • Hugo Araújo
  • José Melo
  • Tiago Nunes
MSc Students
  • André Matos
  • Daniela Valério
  • Eduardo Pinho
  • João Silva
  • Joni Lourenço
  • Rui Mendes
Undergraduate Students
  • Catarina Novo
  • Diogo Corte
  • Diogo Silva
  • Eduardo Duarte
  • Eduardo Sousa
  • Renato Pinho
  • Ricardo Ribeiro
Former PhD Students
  • Luís Ribeiro
  • David Campos
  • Tiago Pedrosa
  • Nuno Rosa
  • Daniel Polónia
  • José Paulo Lousado
  • Miguel Pinheiro
Hello world!

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DICOM Services Over Peer-To-Peer Networks

Funding entity: FCT PTDC/EIA-EIA/104428/2008
Period: 2010-2013

The overall goal is to instantiate a new network connectivity concept for medical imaging data and services at inter-institutional level. This will turn large volumes of clinical information and analytical tools, actually “locked” in clinical units, into shared repositories and high-quality collaborative environments for medical applications, education and research.

EU-ADR project in ua_online

IEETA explora potencialidades das TIC na detecção precoce de reacções adversas a medicamentos
ua_online

GEN2PHEN – Genotype-To-Phenotype Databases: A Holistic Solution

Funding entity: FP7-Health (IP)
Period:
2008-2012

The GEN2PHEN project has the overall ambition of unifying human and model organism genetic variation databases, and doing this in such a way that the resulting holistic view of G2P data can be blended with all other biomedical database domains via one or more central genome browsers.

gen2phen logo

UA.PT Bioinformatics redesign

The University of Aveiro Bioinformatics & Computational Biology group is proud to launch its new online portal to the public. Along with this main portal redesign, new websites were created for Dicoogle and Neoscreen.

XS

XSXS: a FASTQ read simulator

About

XS is a skilled FASTQ read simulation tool, flexible, portable (does not need a reference sequence) and tunable in terms of sequence complexity. XS handles Ion Torrent, Roche-454, Illumina and ABI-SOLiD simulation sequencing types. It has several running modes, depending on the time and memory available, and is aimed at testing computing infrastructures, namely cloud computing of large-scale projects, and testing FASTQ compression algorithms. Moreover, XS offers the possibility of simulating the three main FASTQ components individually (headers, DNA sequences and quality-scores). XS was designed and implemented at IEETA, a research unit of the University of Aveiro, and is available for non-commercial use. For other uses, please send an email to ap@ua.pt.

Citation

Pratas, D., Pinho, A. J., & Rodrigues, J. M. R. (2014). XS: a FASTQ read simulator. BMC research notes, 7(1), 40.

Web download
Download and install from console
wget exon.ieeta.pt/xs/xs.tar.gz
tar -vzxf xs.tar.gz
cd xs
make

from secondary link:

wget http://bioinformatics.ua.pt/wp-content/uploads/2014/02/XS.tar.gz
tar -vzxf XS.tar.gz
cd XS
make

QuARC

Quality of Assemblies by Repeat Compression

 

Download QuARC

HighFCM

HighFCMExploring deep Markov models in genomic data compression using sequence pre-analysis

About

HighFCM is a compression algorithm that relies on a pre-analysis of the data before compression, with the aim of identifying regions of low complexity. This strategy enables to use deeper context models, supported by hash-tables, without requiring huge amounts of memory. As an example, context depths as large as 32 are attainable for alphabets of four symbols, as is the case of genomic sequences. These deeper context models show very high compression capabilities in very repetitive genomic sequences, yielding improvements over previous algorithms. Furthermore, this method is universal, in the sense that it can be used in any type of textual data (such as quality-scores). HighFCM was designed and implemented at IEETA, a research unit of the University of Aveiro, and is available for non-commercial use.

Citation

Diogo Pratas and Armando J. Pinho. “Exploring deep Markov models in genomic data compression using sequence pre-analysis”. Proc. of the European Signal Processing Conference, EUSIPCO 2014, Lisboa, Portugal, September 2014.
DOI: to add.

Download
oralint

Interactome for the Human oral cavity

About
From birth, humans are subject to the colonization and invasion attempts of numerous microorganisms. Although in normal situations, contacting with microbes can support the shaping and development of our immune system, specific situations, such as stress or an unhealthy diet, can render us vulnerable to opportunistic pathogens.
Since the oral cavity is particularly exposed to the environment, it is an anatomic region prone to microbial invasion. Additionally, one of the requirements for bacterial colonization and cellular invasion is the establishment of protein-protein interactions (PPIs) with the host. With this in mind, we aim to develop a computational method for prediction of the oral human-microbial interactome.
Revealing the human-microbial interactome will allow further understanding of the mechanisms behind the onset of oral diseases. Additionally, this knowledge may give insight on key proteins involved in oral infections, which can be used for either diagnosis, as molecular biomarkers, or for treatment, as drug-targets.

Download data
Oral proteins from proteomic studies
Positive Gold Standard PPIs
Dataset train/validation
Interactome – obtained predictions
Cytoscape project

GReEn

mfcompress1

 
Research in the genomic sciences is confronted with the volume of sequencing and resequencing data increasing at a higher pace than that of data storage and communication resources, shifting a significant part of research budgets from the sequencing component of a project to the computational one. Hence, being able to efficiently store sequencing and resequencing data is a problem of paramount importance. We describe GReEn (Genome Resequencing Encoding), a tool for compressing genome resequencing data using a reference genome sequence. It overcomes some drawbacks of the recently proposed tool GRS, namely, the possibility of compressing sequences that cannot be handled by GRS, faster running times and compression gains of over 100-fold for some sequences. GReEn software was designed and implemented at IEETA, a research unit of the University of Aveiro, and is available for non-commercial use. For other uses, please send an email to ap@ua.pt.

 



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