Game theory, biology, and the binding game

Tommi Jaakkola



Biological processes span across vastly different scales and necessarily have to be understood at multiple levels of abstraction.  Towards clarifying the role that computation plays in such understanding, we have recently developed a class of game theoretic models for capturing coordinate operation of DNA binding regulators.  Our work builds in part on the argument that the roles of various molecular interactions cannot be understood in isolation but that it is necessary to also capture the context provided by other mutually constraining processes. Our game theoretic model allocates proteins to neighborhoods of sites, and to sites themselves, in a resource constrained manner, while explicitly capturing coordinate and competitive relations among proteins with affinity to the site or region. We provide examples of known biological subsystems that are naturally translated into our framework, and illustrate predictions that can be derived from the model. The focus of the talk will be on mathematical foundations of the modeling approach and requires little or no biological background.

This is joint work with Luis Perez-Breva, Luis Ortiz, and Chen-Hsiang Yeang.

Speaker Bio:


Tommi S. Jaakkola received the M.Sc. degree in theoretical physics from Helsinki University of Technology, Finland, and Ph.D. from MIT in computational neuroscience. Following a postdoctoral position in computational molecular biology (DOE/Sloan fellow, UCSC) he joined the MIT EECS faculty 1998. His research interests include many aspects of machine learning, statistical inference and estimation in the context of graphical models, and analysis and development of algorithms for various modern estimation problems such as those involving multiple predominantly incomplete data sources. His applied research focuses on problems in computational biology such as transcriptional regulation.