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D4 – Deep Drug Discovery and Deployment

Funding entity: FCT Period: 2018-2021

Funding entity: FCT Period: 2018-2021 D4 proposes the use of state-of-the-art Deep Learning methods to tackle the challenges identified in each of the initial stages of the drug discovery pipeline. The main contribution of this project is the creation of an improved computational pipeline that uses Deep Learning architectures to support the drug discovery process. The pipeline will be implemented within a framework that will be available to the community. Both the final platform and the computational methods will be validated with the close collaboration of the industrial partner, which will apply it to develop novel therapeutics for neurodegenerative amyloid diseases.
EHDEN – European Health Data & Evidence Network

Funding entity: H2020/IMI-JU Period: 2018-2023

Funding entity: H2020/IMI-JU Period: 2018-2023 Presently, Europe is generating unprecedented amounts of patient-level information contained in Electronic Health Record (EHR) systems and other types of health databases. This includes structured data in the form of diagnoses, medication, laboratory test results, etc., and unstructured data in clinical narratives, all of which likely contain invaluable insights into the natural history and burden of disease, its clinical management and outcomes, and wider perspectives on both healthcare and the patient experience of it. It is our ambition to fully leverage these vast volumes of data to improve clinical practice and individual patient outcomes by increasing our understanding of disease and treatment pathways and effects. We will galvanize transparent and reproducible analytics that will generate valid real-world evidence to improve patient care and enable medical outcomes-based research at an unprecedented scale. The Electronic Health Data and Evidence Network (EHDEN) consortium will provide the infrastructure and eco-system to make this ambition come true, supporting the disease-specific projects in the IMI Big Data for Better Outcomes (BD4BO) programme, academia, pharmaceutical, and life sciences, regulatory and allied institutions.
SOCA – Smart Open Campus

Funding entity: Centro 2020

The sensing of the person in physical context enables personalized and predictive responses, and is a major step towards a smarter and safer environment. The main objective of SOCA is to create an open innovation ecosystem where data is gathered from multiple sources, processed, integrated, and made available for applications and users, and that is able to create a service sphere able to assist every individual inside it – from personal health to routine daily chores. For this endeavor, the academic campus will provide the perfect framework to support and trial innovations on the smart city and on the assisted living arenas.


NETDIAMOND – New Targets in Diastolic Heart Failure: from Comorbidities to Personalized Medicine

Funding entity:P2020/PAC

Heart failure (HF) is a highly prevalent syndrome of impaired cardiac function that constitutes the main cause of hospitalization and disability amongst the elderly, a leading cause of mortality, morbidity and resource consumption. HF with preserved ejection fraction (HFpEF) is characterized by preserved ejection, impaired cardiac filling, lung congestion and effort intolerance, accounting for a rising proportion of over 50% of cases due to ageing and increasing incidences of systemic arterial hypertension (SAH), obesity and diabetes mellitus (DM). The current proposal sets forth to address this issue by a mixed strategy of discovery science approach through comprehensive multi-omics studies in plasma and tissues from HFpEF patients and animal models with and without comorbidities (DM, SAH and obesity), and an hypothesis-driven approach focusing on disturbances of cell function and communication in endothelial cells (EC), cardiac fibroblasts (CF), adipocytes and CM. A holistic view of HFpEF and of the role of comorbidities will be achieved by correlating and integrating transcriptomics, proteomics and lipidomics studies with clinical data. The impact on CM and myocardium will be comprehensively assessed in vitro and in vivo. Finally, preclinical testing of functional foods, synthetic antioxidants, enhanced bioavailability putative therapeutic molecules as well as other potentially effective gene targets identified along the project’s course will be assayed.

Multimodal Information Retrieval in Medical Imaging Repositories

Funding entity:FCT

Digital medical imaging systems are, nowadays, essential tools in clinical practice, both in decision supporting and in treatment management. The main objective of this project is to investigate new solutions for extracting, merging and searching over multimodal data, including text (DICOM metadata and diagnosis reports) and image information. Relevance feedback will be also investigated to increase the results quality of the proposed multimodal architecture. It is also our aim to investigate the contribution of semantic information in imaging retrieval and information extraction. We will develop a semantic PACS concept to provide search functionality using context-dependent semantic information.

SCREEN-DR – Image Analysis and Machine Learning Platform for Innovation in Diabetic Retinopathy Screening

Funding entity:FCT (CMU-Portugal)

Diabetic Retinopathy (DR) is a leading cause of blindness in the industrialized world that can be avoided with early treatment, demanding an earlier diagnosis in a stage where the treatment is still possible and effective. DR evolves silently without any visual symptoms, during the early stages of the disease.
Under this context, the vision of the consortium SCREEN-DR is to create a distributed and automatic screening platform for DR, based on the state-of-the-art Information and Communication Technologies (ICT), including advanced Picture Archiving and Communication Systems (PACS) management, Machine Learning and Image Analysis, enabling immediate response from health carers, allowing accurate follow-up strategies, and fostering technological innovation.

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).

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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.

EMIF – European Medical Information Framework

Funding entity: IMI-JU

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.

EMIF Catalogue
EMIF web site

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

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

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.

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

Funding entity: FP7-ICT (STREP)

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

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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.

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, (, 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.

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.

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.

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

Funding entity: FP7-Health (IP)

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.

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