INESC-ID   Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento em Lisboa
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-Bioinformatics and Information Retrieval Data Structures Analysis and Design (II11006)
Acronym: BIRDS
Luis Manuel Silveira Russo
From 01-Jan-2016 to 31-Dec-2020
Financed by: European Commission
Partnerships: ENXENIO, S.L (Company), Helsinki University of Technology (University) - Helsinki , Finland, INESC-ID (Other), National University Corporation. Kyushu (University), Universidade da Coruna (University), Universidade de Concepcion (University), Universidade do Chile (University) - Santiago do Chile, Chile, University of Melbourne (University) - Melbourne, Australia
Members: Luis Manuel Silveira Russo, Arlindo Manuel Limede de Oliveira, Ana Teresa Correia de Freitas, Alexandre Paulo Lourenço Francisco, Jorge dos Santos Oliveira
The overall goal of BIRDS is to establish a long term international network involving leading researchers in bioinformatics and information retrieval from four different continents, to strengthen the partnership though the exchange of knowledge and expertise, and to develop integrated approaches to improve current approaches in both fields. It will be implemented through staff exchanges, in addition to summer schools, workshops and conferences to facilitate knowledge sharing between members of partnership. We will also bring research results to market, thanks to cooperation with an innovative SME software development company based in Europe.
-A COmputational Modelling platform for Epithelial DYnamics to explore the role of epithelial­-mesenchymal transition and stemness acquisition in cancer recurrence (II08021)
Acronym: CoMEDy
Pedro Tiago Gonçalves Monteiro
From 01-Jul-2016 to 30-Jun-2019
Prime Contractor: Fundação Calouste Gulbenkian (Other) - Lisboa, Portugal
Financed by: FCT
Partnerships: Fundação Calouste Gulbenkian (Other) - Lisboa, Portugal, INESC-ID (Other)
Members: Pedro Tiago Gonçalves Monteiro
For most cancers, which stem from epithelial cells, tumour recurrence and metastasis are the major causes of mortality. Albeit extensive research, these processes are still not well understood. However, recent studies point towards the necessity to take into account intra­tumour heterogeneity to design effective therapies.
This proposal relies upon the premise that computational models combining both cellular and micro­environment levels are required to tackle our main goal: to clarify, in the context of carcinomas, the emergence of EMT and CSCs as well as their relationship.
CoMEDy, the computational platform to be developed, will be useful to tackle the modelling of other biological processes that require the consideration of detailed intra­cellular networks and of cell interactions with the micro­environment. The logical model of a comprehensive regulatory network of EMT and stemness, together with its integration in the microenvironment context, will provide new insights into mechanisms of cancer progression. Among the model predictions, those confirmed by our in vitro experiments, should serve as valuable guides to innovative cancer therapies.

-Formal methods for the analysis of modular gEnetic ReGulatOry network DynamiCs (II08020)
Acronym: ERGODiC
Pedro Tiago Gonçalves Monteiro
From 01-Jul-2016 to 30-Jun-2019
Prime Contractor: INESC-ID (Other)
Financed by: FCT (PTDC/EEICTP/2914/2014)
Partnerships: Fundação Calouste Gulbenkian (Other) - Lisboa, Portugal, INESC-ID (Other)
Members: Pedro Tiago Gonçalves Monteiro, Maria Inês Camarate de Campos Lynce de Faria, Pedro do Nascimento Barata Leal Varela
We aim to develop methods to assist modelers in the analysis of logical models of regulatory-signaling networks. In particular, we aim to assess the model's attractors and basins of attraction, including their reachability properties.
To achieve this goal, we will rely on formal methods that have been successfully applied to the development and verification of software and hardware systems, such as Boolean Satisfiability (SAT) and model checking, for the analysis of discrete dynamical systems.
Overall, our proposed developments are expected to provide means for a deeper and comprehensive understanding of how regulatory-signaling networks drive cellular processes. Additionally, even though the results to be achieved in the context of this project have a direct application in the field of Systems Biology, the formal methods supporting those results can benefit all applications based on discrete event systems.

-NEUROCLINOMICS2 - Unravelling Prognostic Markers in NEUROdegenerative diseases through CLINical and OMICS data integration (II11035)
Sara Alexandra Cordeiro Madeira
From 01-Jul-2016 to 30-Jun-2019
Prime Contractor: INESC-ID (Other)
Financed by: FCT
Partnerships: IMM - Instituto Medicina Molecular (University) - Lisboa, Portugal, INESC-ID (Other), Instituto de Telecomunicações (IT) (Other) - Lisbon, Portugal
Members: Sara Alexandra Cordeiro Madeira, Alexandre Paulo Lourenço Francisco, Rui Miguel Carrasqueiro Henriques, Telma Filipa Lucas de Mira Pereira, Andreia Sofia Monteiro Teixeira
The motivation for NEUROCLINOMICS (PTDC/EIA-EIA/111239/2009) was the largely recognized need for integrative approaches allowing a broader study of brain related pathologies. Its contribution emphasized the relevance of inferring relationships within and between heterogeneous sources of omic, clinical, and personal data. In this project, we developed the prototype of a knowledge discovery (KD)system that currently integrates data mining algorithms to unravel biomedical markers.
In NEUROCLINOMICS2, we move towards the challenging tasks of understanding disease progression patterns and predicting prognostic markers for personalized medicine. We now focus on learning prognostic markers through the analysis of multivariate time series, where time points are snapshots of the patient´s condition collected periodically along their follow up. Addressing these challenges will result in new mining algorithms to be integrated in the KD system, which will be upgraded for both desktop and mobile platforms, and continuously updated with new national data from national data from patients follow up and relevant international data from ADNI and ProACT.

-Accelerating progress toward the new era of precision medecine (II11009)
Acronym: PRECISE
Alexandre Paulo Lourenço Francisco
From 01-Dec-2016 to 30-Nov-2019
Prime Contractor: INESC-ID (Other)
Financed by: FCT
Partnerships: IMM - Instituto Medicina Molecular (University) - Lisboa, Portugal, INESC-ID (Other), IST-ID (University) -Portugal
Members: Arlindo Manuel Limede de Oliveira, Mário Jorge Costa Gaspar da Silva, José Luis Brinquete Borbinha, Alexandre Paulo Lourenço Francisco, Luís Jorge Brás Monteiro Guerra e Silva
PRECISE is a joint research program that aims to accelerate progress of Portuguese health care toward the new era of precision medicine. We believe this is the right time to start broadly applying the concept of prevention and treatment strategies that take individual variability into account, so that one day all patients will be offered customized care with treatments that match each individual´s molecular profile and personal history. The PRECISE joint research program seeks to create tangible
Benefits for Portuguese citizens. Reflecting this ambition, we are putting together a plan that capitalizes on recent development of large-scale biological databases, powerful methods for characterizing patients as the molecular level, and computational tools for analyzing large sets of data. Science is catapulting medicine forward by providing massive amounts of data each individual and the ultimate challenge is how to use all that data to better guide clinical practice.

-BacGenTrack - An integrated system for Bacterial Genome Tracking using high throughput sequencing technology: from identification to visualization (II11012)
Acronym: BacGenTrack
Alexandre Paulo Lourenço Francisco
From 01-Dec-2016 to 30-Nov-2019
Prime Contractor: Instituto de Medicina Molecular (Other) - Lisboa, Portugal
Financed by: FCT
Partnerships: IMM - Instituto Medicina Molecular (University) - Lisboa, Portugal
Members: Alexandre Paulo Lourenço Francisco, Cátia Raquel Jesus Vaz
High throughput sequencing (HTS) provides researchers the ultimate tool to analyze outbreaks and study bacterial determinants of virulence resistance. However data analysis is demanding in computational terms and expertise. We propose to implement a user-friendly web system and novel analysis algorithms needed to facilitate the analysis and provide the essential data sharing tools necessary for its effective use in the field of Molecular Epidemiology.
-Portuguese Biological Data Network (II11014) (Project Link)
Acronym: BioData
Arlindo Manuel Limede de Oliveira
From 01-Jan-2017 to 31-Dec-2019
Prime Contractor: Fundação Calouste Gulbekian (Other)
Financed by: P2020
Partnerships: APBIO (Other) -Portugal, CCMAR (Other) -Portugal, Fundação Champalimaud (Other), IBET (Other), IBMC (Other) -Portugal, INESC-ID (Other), Instituto Superior Técnico (University) - Lisboa, Portugal, ITQB (Other), Universidade do Minho (University) - Braga, Portugal
Members: Pedro Tiago Gonçalves Monteiro, Mário Jorge Costa Gaspar da Silva, Arlindo Manuel Limede de Oliveira is the Portuguese distributed infrastructure for biological data, to be included in FCT’s Infrastructure Road Map of 2013., a national bioinformatics network manages the Portuguese node of ELIXIR (European Life Sciences Infrastructure for Biological Information).ELIXIR’s vision for the future is to provide researchers in academia and industry with seamless access to biological information that will revolutionise discovery in the life sciences, by integrating data at different levels of analysis, for example from molecular biology to industrial solutions. shares these goals and aims to catalyse this access and translation at the regional and national level, as well as contributing to ELIXIR efforts at the European level.In its nature is transversal to all of the life sciences, and will likely be relevant for other proposals for inclusion in this infrastructures roadmap. It is organised around a general scientific, technical and educational platform, an industry and entrepreneurship program and a focus on specialised areas of knowledge and application, described below. The choice of these specialised areas aims to start building this infrastructure capitalising on existing excellence in research and institutions, bridging to international projects (e.g. EMBRC) and a potential for application and translation to the economy.
-Personalizing cancer therapy through integrated modeling and decision (II11039) (Project Link)
Susana de Almeida Mendes Vinga Martins
From 01-Sep-2018 to 09-Jun-2019
Prime Contractor: Instituto de Engenharia Mecânica (Pólo IST) (Other)
Financed by: FCT
Partnerships: Centro Hospitalar de Lisboa Norte (Other), FCiências.ID - Associação para a Investigação e Desenvolvimento de Ciências (Other), INESC-ID (Other), Instituto de Engenharia Mecânica (Other) - Lisbon, Portugal, Instituto de Medicina Molecular (Other) - Lisboa, Portugal, Instituto de Telecomunicações (IT) (Other) - Lisbon, Portugal
Members: Susana de Almeida Mendes Vinga Martins, André Filipe da Silva Veríssimo
The goal of project Perseids is to create accurate classifiers and to identify factors associated with disease outcome, which in turn will support the design of adaptive controllers and decision systems. The ultimate aim is to develop robust clinical decision support systems for personalized cancer therapy optimization by integrating patient multilevel data.
-Ferramentas para análise filogenetica em larga escala (II11019) (Project Link)
Acronym: NGPHYLO
Alexandre Paulo Lourenço Francisco
From 01-Oct-2018 to 10-Sep-2021
Prime Contractor: INESC-ID (Other)
Financed by: FCT
Partnerships: INESC-ID (Other), Instituto de Medicina Molecular (Other) - Lisboa, Portugal
Members: Alexandre Paulo Lourenço Francisco, Cátia Raquel Jesus Vaz, Luis Manuel Silveira Russo
The current ability to rapidly sequence whole microbial genomes is revolutionizing microbiology and epidemiological surveillance, with high impact on the identification of antimicrobial resistance genes and virulence factors, or on the detection of outbreaks in hospital settings or in the food industry, e.g., by monitoring the spread of antimicrobial resistance, an ever growing concern. It has allowed also more complex phylogenetic analyses based on the whole genome data. The bottleneck has however shifted to data analysis problems. From a computational point of view, a growing concern is how algorithms and tools can be scaled up to analyse thousands of genetic loci in thousands of isolates. This project aims then to: (1) research and design efficient and scalable data structures and algorithms that allow phylogenetic analyses at large scales; (2) develop tools suitable for processing large scale phylogenetic analysis, deployable in cloud and HPC environments; (3) make tools available as reusable components, enabling the construction of more complex parametrizable pipeline workflows; (4) develop and integrate intuitive and user-friendly interfaces.
-Inibição da patogénese e construção de fábricas celulares: por desenvolvimento de modelos regulatórios-metabólicos mistos à escala do genoma em leveduras (II08027)
Acronym: MIXEDUP
Pedro Tiago Gonçalves Monteiro
From 01-Oct-2018 to 31-Dec-2020
Prime Contractor: IST-ID (University) -Portugal
Financed by: FCT
Partnerships: Fundação Calouste Gulbekian (Other), INESC-ID (Other), IST-ID (University) -Portugal, Universidade do Minho (University) - Braga, Portugal
Members: Pedro Tiago Gonçalves Monteiro
This project proposes to use Systems Biology approaches and single cell eukaryotes as case studies, in order to design better ways to prevent and control superficial and invasive candidiasis, whose two prime causes are C. albicans and C. glabrata. Genome-scale regulatory models will be built for C. albicans and C. glabrata, using the data gathered at the PathoYeastract database, and the S. cerevisiae regulatory model as a cast ( Also, orthology relationships will be considered, extracted from CGD ( and PhylomeDB ( Finally, a reliable complete genome-scale integrated regulatory-metabolic model will be considered, connecting the metabolic and regulatory models for each of the three yeast species.