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Clustering of genes into regulons using integrated modeling-COGRIM.


ABSTRACT: We present a Bayesian hierarchical model and Gibbs Sampling implementation that integrates gene expression, ChIP binding, and transcription factor motif data in a principled and robust fashion. COGRIM was applied to both unicellular and mammalian organisms under different scenarios of available data. In these applications, we demonstrate the ability to predict gene-transcription factor interactions with reduced numbers of false-positive findings and to make predictions beyond what is obtained when single types of data are considered.

SUBMITTER: Chen G 

PROVIDER: S-EPMC1839128 | biostudies-literature | 2007

REPOSITORIES: biostudies-literature

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Clustering of genes into regulons using integrated modeling-COGRIM.

Chen Guang G   Jensen Shane T ST   Stoeckert Christian J CJ  

Genome biology 20070101 1


We present a Bayesian hierarchical model and Gibbs Sampling implementation that integrates gene expression, ChIP binding, and transcription factor motif data in a principled and robust fashion. COGRIM was applied to both unicellular and mammalian organisms under different scenarios of available data. In these applications, we demonstrate the ability to predict gene-transcription factor interactions with reduced numbers of false-positive findings and to make predictions beyond what is obtained wh  ...[more]

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