Prof Pedro Mendes - research
My research is in the area of computational systems biology, which aims to better understand biological systems through the use of computer models. I am a member of the Manchester Centre for Integrative Systems Biology, and of the Machine Learning and Optimization research group. My active areas of research are:
- Development of modelling and simulation software: I am the author of the popular simulator Gepasi and leader of the new COPASI simulator (w/ U. Kummer). I have also been actively involved in the development of SBML, the systems biology markup language, and the MIRIAM proposal for model annotation.
- Construction of biochemical models: I am currently working on models of the yeast pentose phosphate pathway, mammalian iron metabolism, eukaryotic translation. I am also developing methods for the construction of large-scale kinetic models of entire cells.
- Parameter estimation and systems identification: I have pioneered the application of numerical global optimization in biochemical kinetic modelling. I am interested in using formal systems identification techniques in systems biology, particularly for reverse engineering models from data.
- Reverse engineering biological networks: a long-term objective of systems biology is to be able to construct models directly from large-scale genomics, proteomics and metabolomics data sets. I have been interested in this for a while and have been involved in developing several algorithms to this effect. I have also created many artificial networks to benchmark these problems (eg the AGN system).
- 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) predefined behaviours.
Research in the areas listed above requires a broad interdisciplinary approach and I work with people from most areas of science, either in my own research group or as collaborators.