Visual systems biology: design, understand, organize

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• Lorenzo Dematté, CoSBi
• Tuesday 10 March 2009, 14:00-15:00
• Large public lecture room, Microsoft Research, Roger Needham Building, 7 J J Thomson Avenue, Cambridge CB3 0FB.

If you have a question about this talk, please contact Dr Fabien Petitcolas.

Abstract: Programming language-based approaches to systems biology allow us to model biological systems in an “algorithmic” way, enabling the use of well-established computing techniques that deal with program analysis, composition and verification, integrated development environments and debugging tools. However, many of these techniques and principles require too much expertise to be used by a non-tech audience. Furthermore, the output of current Systems Biology tools (simulators, analyzers, compilers) is in most cases in the form of text and charts, while biologists are more accustomed at using diagrams, tables, reaction graphs and rich graphics. In this talk I will present how the usage of visual tools can enrich Systems Biology at many levels: model definition, understanding, testing and debugging; visualization of output; design of in-silico experiments. Many of these ideas are not new to computer scientists and developers, but if a combination of techniques will prove to be suitable for understanding complex biological systems, our hope is that they could be adapted to ease the development of complex and concurrent software as well.

Biography: Lorenzo Dematté attended the Faculty of Science at the University of Trento, where he obtained a Bachelor’s degree (2001) and a Master’s degree (2005) in Computer Science. His thesis, “Concurrency programming by Contracts,” focused on exploring new paradigms for concurrent and distributed programming. From May 2005 to September 2006 he worked in the Bioinformatics department at the IASMA research center on the prediction of functions and interactions between proteins as part of the Grapevine Genome Project.

This talk is part of the CoSBi Computational and Systems Biology Series series.

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