Pedro Pedrosa Mendes is a Professor of Computational Systems Biology in the School of Computer Science at the University of Manchester. He is a member of the Manchester Centre for Integrative Systems Biology (MCISB), the Machine Learning and Optimization (MLO) group. He is also a Professor at the University of Connecticut Health Center.
Mendes did his undergraduate degree in Biochemistry at the University of Lisbon. He then moved to the UK and was awarded a Doctor of Philosophy from Aberystwyth University in 1994 for work on computer simulation of metabolic pathways.
Following his PhD, Mendes moved to the National Center for Genome Resources for a year then on to the Virginia Bioinformatics Institute (VBI) of Virginia Polytechnic Institute and State University (Virginia Tech or VT) in 2000. He moved to the University of Manchester as Professor in 2007, while still keeping a 20% appointment in the VBI until the end of 2013. In January 2014 he joined the Center for Quantitative Medicine at the University of Connecticut Health Center and he splits his time 50/50 with the appointment at the University of Manchester.
Mendes research is concerned with computational systems biology, which aims to better understand biological systems through the use of computer models. He is the author of the biochemical simulator GEPASI (General Pathway Simulator) and leader of the new COPASI (COmplex PAthway SImulator) simulator. He has also been actively involved in the development of the Systems Biology Markup Language (SBML), and MIRIAM (Minimum Information Required in the Annotation of Models). His research group work on problems in the following areas:
Construction of biochemical models Mendes is currently working on models of the yeast pentose phosphate pathway, oxidative stress response in yeast and breast cancer cells.
Parameter estimation Mendes has applied numerical global optimization in biochemical kinetic modelling and parameter estimation. He is interested in using formal systems identification techniques in systems biology, particularly for reverse engineering models from data.
Reverse engineering biological networks Mendes has been involved in systems biology through the construction of metabolic models directly from large-scale genomics, proteomics and metabolomics data sets. Mendes group has created artificial networks to benchmark these problems. for example the Artificial Gene Network system.
Data integration and Data fusion systems biology and metabolic engineering produces large amounts of data that originated in a diversity of techniques. The Mendes group works on integrating biochemical data and also works on data fusion, numerical issues of data integration.
Biological data mining using machine learning to analyse the large amounts of data produced in systems biology experiments, such as looking for common or unusual patterns in those data, or to classify (and identify the determinants) of predefined behaviours.
Mendes research has been funded by the Biotechnology and Biological Sciences Research Council (UK), National Science Foundation (USA), National Institutes of Health (USA) and the European Commission.