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Executable Strategies for Cellular Decision Making

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If you have a question about this talk, please contact Danielle Stretch.

As time goes by, it becomes more and more apparent that the puzzles of life involve more and more molecular pieces that fit together in increasingly complex ways. We know that Biology is not an exact science. It is messy and noisy, and most often vague and ambiguous; posing great difficulties to establish mathematical and computational methods for its analysis. To make matters worse (so to speak), the combinatorial complexity observed in biological networks (e.g., metabolic and signalling pathways) is staggering, which renders the comprehension and analysis of such systems a major challenge. Recent efforts to create executable models of complex biological phenomena entail great promise for new scientific discoveries, shading new light on the puzzle of life. We distinguish between two types of biological models mathematical and computational which differ in their representations of biological phenomena. We call the approach of constructing computational models of biological systems Executable Biology, as it focuses on the design of executable computer algorithms that mimic biological phenomena. In this talk, I will survey the main modelling efforts in this direction (e.g., Boolean networks, process calculi, Petri nets, interacting state-machines), emphasize the applicability and benefits of executable models in biological research, mainly through models of cell fate determination processes governed by cancer-related signalling pathways (e.g., EGFR , Notch, Wnt), and highlight some of the main challenges that executable biology poses for Biology, medical research, and Computer Science.

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

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