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Functions and mappings / Markov models / Sequence motif / Function / Maximum likelihood / Markov chain / Vector space / Matrix / Multiple EM for Motif Elicitation / Mathematics / Algebra / Bioinformatics


Discovery of Conserved Sequence Patterns Using a Stochastic Dictionary Model Mayetri Gupta and Jun S. Liu Detection of unknown patterns from a randomly generated sequence of observations is a problem arising in Ž elds r
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Document Date: 2004-07-21 15:42:09

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Facility

Harvard University / /

IndustryTerm

favorable binding energy / undetected motif site / gene regulatory networks / factor binding site / signal processing / possible site / motif site / search space / stochastic alignment algorithm / /

Organization

Harvard University / National Science Foundation / American Statistical Association / Department of Statistics / U.S. Securities and Exchange Commission / /

Person

Jun S. Liu / Xiao-Li Meng / Hao Li / /

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Position

associate editor for helpful comments / vp / vp 5T / Professor / Stochastic Dictionary Model / messenger / /

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FP / /

PublishedMedium

Journal of the American Statistical Association / /

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P4x5 D FM / C FM / 13 FM / FM 411 / /

Technology

MobyDick algorithm / gene expression / stochastic alignment algorithm / Simulation / SDDA algorithm / EM algorithm / Gibbs sampling algorithm / /

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