Emanuel Gonçalves

Emanuel Gonçalves

Phd Student - Saez-Rodriguez research group

I studied computer science (bachelor degree) and then bioinformatics (master degree) at University of Minho, Portugal. During my studies I took part in several computer science projects and later on I focused in projects related with Bioinformatics and Systems Biology. Consequently, I become familiar with several programming languages, in particular with those that follow the object-oriented paradigm, e.g. Java and C#. During my master I became a member of the bioinformatics group at University of Minho and developed work related with in silica strain optimisation based on over and under expression of genes. On the last year of my master I was granted a trainee position at EMBL-EBI in Saez-Rodriguez Group, where I did my master thesis that focused on the integration of logic modelling and visualisation tools. Now in my PhD project, I intend to focus on the implementation of novel approaches to link different types of biological networks, i.e. link signalling, regulatory and metabolic networks, to increase the predictive power of in silico models. We will address problems like: how to couple the different mathematical formalisms used to represent each layer, or how can we simulate the integrated model?

ORCID iD: 0000-0002-9967-5205

Tel:+ 44 (0) 1223 49 2641 / Fax:+ 44 (0) 1223 494 468

Publications

2013

Bridging the layers: towards integration of signal transduction, regulation and metabolism into mathematical models.
Gonçalves E, Bucher J, Ryll A, Niklas J, Mauch K, Klamt S, Rocha M, Saez-Rodriguez J.
Molecular bioSystems Volume 9 (2013) p.1576-1583

DvD: An R/Cytoscape pipeline for drug repurposing using public repositories of gene expression data.
Pacini C, Iorio F, Gonçalves E, Iskar M, Klabunde T, Bork P, Saez-Rodriguez J.
Bioinformatics (Oxford, England) Volume 29 (2013) p.132-134

CySBGN: a Cytoscape plug-in to integrate SBGN maps.
Gonçalves E, van Iersel M, Saez-Rodriguez J.
BMC bioinformatics Volume 14 (2013) p.17

2012

CellNOptR: a flexible toolkit to train protein signaling networks to data using multiple logic formalisms.
Terfve C, Cokelaer T, Henriques D, MacNamara A, Goncalves E, Morris MK, van Iersel M, Lauffenburger DA, Saez-Rodriguez J.
BMC systems biology Volume 6 (2012) p.133

Optimization approaches for the in silico discovery of optimal targets for gene over/underexpression.
Gonçalves E, Pereira R, Rocha I, Rocha M.
Journal of computational biology : a journal of computational molecular cell biology Volume 19 (2012) p.102-114