Seminario: “Answering questions in biology and medicine by making inferences on networks”

Lunedì 11 Febbraio 2019, ore 10:00 - Aula 2BC60 - Alberto Paccanaro


Lunedì 11 Febbraio 2019 alle ore 10:00 in Aula 2BC60, Alberto Paccanaro (Royal Holloway University of London) terrà un seminario dal titolo “Answering questions in biology and medicine by making inferences on networks”.

An important idea that has emerged recently is that a cell can be viewed as a set of complex networks of interacting bio-molecules and genetic disease is the result of abnormal interactions within these networks. In this talk, I'll present novel computational methods for answering questions in systems biology and medicine which can all be phrased in terms of inference and structure discovery in such large scale networks. These methods are based and extend recent developments in the areas of machine learning (particularly semi-supervised learning and matrix factorization), graph theory and network science. I’ll show how these computational techniques can provide effective solutions for: 1) quantifying similarity between heritable diseases at molecular level using exclusively disease phenotype information; 2) disease gene prediction; 3) drug side-effect prediction.

Alberto Paccanaro is full Professor in Machine Learning and Computational Biology in the Department of Computer Science at Royal Holloway University of London where he is also Director of the Centre for Systems and Synthetic Biology. He completed his undergraduate studies in Computer Science at the University of Milan 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 in Mansoor Saqi’s lab at Queen Mary University of London and then in Mark Gerstein’s lab at Yale University. His research interests are in applying and developing machine learning and pattern recognition techniques for solving problems in molecular biology and medicine. His recent work has focused on the development of methods for analysis and inference in large scale biological networks.