DNA Binding and Games
Author(s)Perez-Breva, Luis; Ortiz, Luis E.; Yeang, Chen-Hsiang, 1969-; Jaakkola, Tommi
Tommi's Machine Learning
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We propose a game-theoretic approach tolearn and predict coordinate binding of multiple DNA bindingregulators. The framework implements resource constrainedallocation of proteins to local neighborhoods as well as to sitesthemselves, and explicates coordinate and competitive bindingrelations among proteins with affinity to the site or region. The focus of this paper is on mathematical foundationsof the new modeling approach. We demonstrate the approachin the context of the lambda-phage switch, a well-known biologicalsubsystem, and provide simulation results that successfully illustrate the predictions that can be derived from the modelwith known structure and affinities. Subsequentwork will elaborate on methods for learning the affinities and gamestructures from available binding data.
Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory