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Chris H Wiggins

Showing results (1-10 of 40) with videos related to

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IEEE Transactions on Pattern Analysis and Machine Intelligence|May 1, 2010
An information-theoretic derivation of min-cut-based clusteringAnil Raj, Chris H Wiggins
Annals of the New York Academy of Sciences|October 11, 2007
Benchmarking of dynamic Bayesian networks inferred from stochastic time-series dataLawrence A David, Chris H Wiggins
Physical Review Letters|July 23, 2008
Bayesian approach to network modularityJake M Hofman, Chris H Wiggins
Proceedings of the National Academy of Sciences of the United States of America|February 25, 2005
Inferring network mechanisms: the Drosophila melanogaster protein interaction networkManuel Middendorf, Etay Ziv, Chris H Wiggins
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|May 21, 2005
Information-theoretic approach to network modularityEtay Ziv, Manuel Middendorf, Chris H Wiggins
Plos One|October 25, 2007
Optimal signal processing in small stochastic biochemical networksEtay Ziv, Ilya Nemenman, Chris H Wiggins
Physical Review Letters|September 28, 2010
Information-optimal transcriptional response to oscillatory drivingAndrew Mugler, Aleksandra M Walczak, Chris H Wiggins
Proceedings of the National Academy of Sciences of the United States of America|April 9, 2009
A stochastic spectral analysis of transcriptional regulatory cascadesAleksandra M Walczak, Andrew Mugler, Chris H Wiggins
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|November 13, 2009
Spectral solutions to stochastic models of gene expression with bursts and regulationAndrew Mugler, Aleksandra M Walczak, Chris H Wiggins
Methods in Molecular Biology (Clifton, N.J.)|January 31, 2013
Analytic methods for modeling stochastic regulatory networksAleksandra M Walczak, Andrew Mugler, Chris H Wiggins
Pageof 4

Showing results (1-10 of 40) with videos related to

Sort By:
Pageof 4
IEEE Transactions on Pattern Analysis and Machine Intelligence|May 1, 2010
An information-theoretic derivation of min-cut-based clusteringAnil Raj, Chris H Wiggins
Annals of the New York Academy of Sciences|October 11, 2007
Benchmarking of dynamic Bayesian networks inferred from stochastic time-series dataLawrence A David, Chris H Wiggins
Physical Review Letters|July 23, 2008
Bayesian approach to network modularityJake M Hofman, Chris H Wiggins
Proceedings of the National Academy of Sciences of the United States of America|February 25, 2005
Inferring network mechanisms: the Drosophila melanogaster protein interaction networkManuel Middendorf, Etay Ziv, Chris H Wiggins
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|May 21, 2005
Information-theoretic approach to network modularityEtay Ziv, Manuel Middendorf, Chris H Wiggins
Plos One|October 25, 2007
Optimal signal processing in small stochastic biochemical networksEtay Ziv, Ilya Nemenman, Chris H Wiggins
Physical Review Letters|September 28, 2010
Information-optimal transcriptional response to oscillatory drivingAndrew Mugler, Aleksandra M Walczak, Chris H Wiggins
Proceedings of the National Academy of Sciences of the United States of America|April 9, 2009
A stochastic spectral analysis of transcriptional regulatory cascadesAleksandra M Walczak, Andrew Mugler, Chris H Wiggins
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|November 13, 2009
Spectral solutions to stochastic models of gene expression with bursts and regulationAndrew Mugler, Aleksandra M Walczak, Chris H Wiggins
Methods in Molecular Biology (Clifton, N.J.)|January 31, 2013
Analytic methods for modeling stochastic regulatory networksAleksandra M Walczak, Andrew Mugler, Chris H Wiggins
Pageof 4