“Inference and structure discovery in protein interaction networks”

Speaker: Alberto Paccanaro

Professor in Machine Learning & Computational Biology
Centre for Systems and Synthetic Biology & Department of Computer Science
Royal Holloway, University of London

Abstract: An important idea that has emerged recently is that a cell can be viewed as a complex network of interrelating proteins, nucleic acids and other bio-molecules.  At the same time, data generated by large-scale experiments often have a natural representation as networks such as protein-protein interaction networks, genetic interaction networks, co-expression networks. From a computational point of view, a central objective for systems biology is therefore the development of methods for making inferences and discovering structure in biological networks possibly using data which are also in the form of networks.In this talk, I’ll present novel computational methods for solving biological problems which can all be phrased in terms of inference and structure discovery in large scale networks. These methods are based and extend recent developments in the areas of machine learning (particularly semi-supervised learning), graph theory and network science. I will show how these computational techniques can provide effective solutions for: de-noising large scale protein-protein interaction experiments; detecting protein complexes from protein-protein interaction data. Finally, I’ll describe how these ideas could be applied to problems in the area of Network Medicine, such as disease gene prediction and drug repositioning.

Bio: Alberto Paccanaro is Professor in Computational Biology at Royal Holloway, University of London. He completed his undergraduate studies in Computer Science at the University of Milan in 1990 and received his PhD from the University of Toronto in 2002, specializing in machine learning under the supervision of Geoffrey Hinton. From 2002 to 2006 he was a postdoc at Queen Mary University of London and Yale University. His research interests are in applying and developing machine learning and pattern recognition techniques for solving problems in molecular biology. His recent work has focused on the development of methods for analysis and inference in large scale biological networks.

Homepage: www.cs.rhul.ac.uk/~alberto

Lab page: www.paccanarolab.org

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