INESC-ID   Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento em Lisboa
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-Towards a semi-automatic model revision of logical regulatory network (II08019)
Acronym: IFCT
Pedro Tiago Gonçalves Monteiro
From 01-Jan-2015 to 31-Dec-2018
Prime Contractor: IF/01333/2013/CP1 204/CT0001 (Other)
Financed by: FCT
Partnerships: INESC-ID (Other)
Members: Pedro Tiago Gonçalves Monteiro
The foremost question in Systems Biology is how to interpret vast amount of multiscale data, in order to predict and explain the behavior of complex biological systems. The present proposal addresses this question and is subdivided into two main interconnected parts: methods and applications.
A comparative genomics approach will be used among closely related species, for the identification of a comprehensive regulatory network scaffold (top-down). Then starting with homologous regulatory elements we will proceed with the definition of a logical model (bottom-up), complemented with formal verification techniques for model analysis and validation.
Additionally, methods aimed at the full characterization of complex cyclic attractors, which is still an open problem, will be developed using the circuit functionality contexts.
These methods will be applied to the prediction of Multidrug Resistance in yeasts due to its importance on the control of highly opportunistic pathogen on human impaired immune system [20]. Also, using the Segment Polarity cross-regularity module to simulate a 2D grid cross-signaling of cells O will push the limits of current logical regulatory networks.

 
-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.
 
-Deciphering the mechanisms of transcriptional regulation that control antifungal drug resistance in pathogenic yeast Candida glabrata: aiming at the development of improved diagnosis and therapeutic (II08022)
Acronym: CANTROL
Pedro Tiago Gonçalves Monteiro
From 01-Mar-2016 to 28-Feb-2019
Prime Contractor: IST-ID (University) -Portugal
Financed by: FCT
Partnerships: Faculdade de Medecina da Universidade do Porto (University) - Porto, Portugal, Fundação Calouste Gulbenkian (Other) - Lisboa, Portugal, INESC-ID (Other), IST-ID (University) -Portugal
Members: Pedro Tiago Gonçalves Monteiro
Results obtained within this project are expected to shed light into MDR regulation mechanisms in fungal pathogens and their clinical implications. The gathered knowledge is also expected to guide the delineation of strategies to surpass the widespread of multidrug resistance among fungal pathogens with implications in Human Health and Biotechnology.
 
-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)
Acronym: NEUROCLINOMICS2
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-Sep-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.