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DNA Binding and Games

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dc.contributor.advisor Tommi Jaakkola
dc.contributor.author Perez-Breva, Luis
dc.contributor.author Ortiz, Luis E.
dc.contributor.author Yeang, Chen-Hsiang
dc.contributor.author Jaakkola, Tommi
dc.contributor.other Tommi's Machine Learning
dc.date.accessioned 2006-03-10T01:22:50Z
dc.date.available 2006-03-10T01:22:50Z
dc.date.issued 2006-03-06
dc.identifier.other MIT-CSAIL-TR-2006-018
dc.identifier.uri http://hdl.handle.net/1721.1/31311
dc.description.abstract 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.
dc.description.provenance Made available in DSpace on 2006-03-10T01:22:50Z (GMT). No. of bitstreams: 2 MIT-CSAIL-TR-2006-018.ps: 15597128 bytes, checksum: 94e40d6b2f8e02d2241eab8df1708cc8 (MD5) MIT-CSAIL-TR-2006-018.pdf: 598367 bytes, checksum: 30c1e4ed2443b1a368b9e4c3b343039c (MD5) en
dc.format.extent 11 p.
dc.format.extent 15597128 bytes
dc.format.extent 598367 bytes
dc.format.mimetype application/postscript
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.relation.ispartofseries Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory
dc.title DNA Binding and Games

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