Sara C. Madeira

junior fellow
EURIAS cohort 2015/2016
discipline Computer Science and Engineering
Assistant Professor, Instituto Superior Técnico, University of Lisbon

Research project

PROCLINOMICS - Unravelling prognostic markers in complex diseases using clinical and omics data


Complex diseases, such as neurodegenerative diseases, present unique challenges to medicine due to their devastating effect on patients and their families, and socio-economic impact in modern societies. As such, identifying disease risk profiles together with understanding the individualized disease diagnostic and prognostic patterns, is top priority on ongoing research. In this context, high throughput technologies introduced a major change in biology and medical research paradigms. Systems biology has been successfully studying omics, aimed at a fundamental understanding of biological processes and modeling of biological networks. However, it has focused primarily on the molecular scale disregarding the effects of physiology and its enormous variation among individuals, produced by the interaction of each person’s biology and experiences through life. Systems medicine, on the other hand, has recently emerged as the application of systems biology to human health, by incorporating clinical information into its models. Moreover, several authors emphasised the need for integrative approaches, able to infer relationships between omics, clinical, and personal data, to provide a broader understanding of complex diseases. Promising attempts integration wise are arising but no effective integrative approaches between clinical and omics data exist.


This project plans to further study and develop methods for prognostic prediction in complex diseases based on biomedical data analysis (omics and clinical), where data are characterized by a set of heterogeneous biomarkers collected for patients during their follow-up. This is the type of data made available by international consortiuns, such as Alzheimer’s Disease Neuroimaging Initiative (ADNI) and Pooled Resource Open-Access ALS Clinical Trials Database (PRO-ACT), and analysed in NEUROCLINOMICS, a grant funded project I coordinate in Portugal, with a focus on clinical data and neurodegenerative diseases. The motivation for this proposal is the fact that, the efficient analysis, from a temporal perspective, of this type of heterogeneous and multidimensional data, composed by a set of snapshots collected periodically for a set of patients (follow-up), where each snapshot corresponds to the analysis of an heterogeneous set of biomarkers, has been little explored, besides its recognized importance to the discovery of patients’ profiles and progression patterns that can be effectively used to develop automatic prognostic methods.




SARA C. MADEIRA is an Assistant Professor at the Computer Science and Engineering department at Instituto Superior Técnico (IST), Universidade de Lisboa, since 2009, where she teaches undergraduate courses on algorithms and data structures and graduate courses on computational biology and integrative bioinformatics. She is also a senior researcher at INESC-ID, Lisbon, where she received the INESC-ID Young Research Award in 2013.


She received her PhD degree in Computer Science and Engineering at IST in 2008, her MSc degree in Computer Science and Engineering at IST in 2002, and graduated in Matemática-Informática at Universidade da Beira Interior (UBI), in 2000. She was a Lecturer and an Assistant Professor at the Informatics Department of UBI, from 2002-2008 and 2008-2009, respectively.


Her research interests include algorithms and data structures, data mining, machine learning, bioinformatics and medical informatics. In this context, she was the PI of NEUROCLINOMICS - Understanding NEUROdegenerative diseases through CLINical and OMICS data (PTDC/EIA-EIA/111239/2009), a research project embracing the challenges of studying complex diseases and developing efficient and effective mining algorithms for biomedical data, using Amyotrophic Lateral Sclerosis and Alzheimer's disease as case studies. Following this project, she is currently the PI of NEUROCLINOMICS2 - Unravelling Prognostic Markers in NEUROdegenerative diseases through CLINical and OMICS data integration (PTDC/EEI-SII/1937/2014).


Selected publications


'Integrative biomarker discovery in neurodegenerative diseases', with A. V. Carreiro, A. de Mendonça & M. de Carvalho, WIREs Systems Biology and Medicine, Willey doi: 10.1002/wsbm.1310, published online July 2015.


'A Structured View on Patern Mining-based Biclustering’, with R. Henriques & C. Antunes, Pattern Recognition, vol. 48, no. 12, pp. 3941-3958, 2015.


‘Biclustering with Flexible Plaid Models to Unravel Interactions between Biological Processes’, with R. Henriques, IEEE/ACM Transactions on Computacional Biology and Bioinformatics [online], vol. 12, no. 4, pp. 738-752, 2015


‘BicPAM: Pattern-based Biclustering for Biomedical Data Analysis’, with R. Henriques, Algorithms for Molecular Biology, vol. 9, no. 27, 2014.


‘LateBiclustering: Efficient Heuristic Algorithm for Time-Lagged Bicluster Identification’, with J.P. Gonçalves, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 11, no. 5, pp. 801-813, 2014.


‘Identification of Regulatory Modules in Time Series Gene Expression Data using a Linear Time Biclustering Algorithm’, with M.C. Teixeira, I. Sá Correia & A.L. Oliveira, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 7, no.1, pp. 153-165, 2010.


‘Biclustering algorithms for biological data analysis: a survey’, with A.L. Oliveira, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 1, no. 1, pp. 24-45, 2004.



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