CUED Publications database

Discovering transcriptional modules by Bayesian data integration.

Savage, RS and Ghahramani, Z and Griffin, JE and de la Cruz, BJ and Wild, DL (2010) Discovering transcriptional modules by Bayesian data integration. Bioinformatics, 26. i158-i167.

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Abstract

We present a method for directly inferring transcriptional modules (TMs) by integrating gene expression and transcription factor binding (ChIP-chip) data. Our model extends a hierarchical Dirichlet process mixture model to allow data fusion on a gene-by-gene basis. This encodes the intuition that co-expression and co-regulation are not necessarily equivalent and hence we do not expect all genes to group similarly in both datasets. In particular, it allows us to identify the subset of genes that share the same structure of transcriptional modules in both datasets.

Item Type: Article
Uncontrolled Keywords: Bayes Theorem Binding Sites Gene Expression Profiling Multigene Family Oligonucleotide Array Sequence Analysis Saccharomyces cerevisiae Proteins Transcription Factors
Subjects: UNSPECIFIED
Divisions: Div F > Computational and Biological Learning
Depositing User: Cron Job
Date Deposited: 07 Mar 2014 11:33
Last Modified: 29 Nov 2014 23:45
DOI: 10.1093/bioinformatics/btq210