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Decoding human regulatory circuits

delete2004-10-01
delete90
delete
OA
AI
W
William A. Thompson
M
Michael J. Palumbo
W
Wyeth W. Wasserman
J
Jun S. Liu
C
Charles E. Lawrence
DOI：10.1101/gr.2589004delete
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Abstract

Abstract

En 中文
Clusters of transcription factor binding sites (TFBSs) which direct gene expression constitute cis-regulatory modules (CRMs). We present a novel algorithm, based on Gibbs sampling, which locates, de novo, the cis features of these CRMs, their component TFBSs, and the properties of their spatial distribution. The algorithm finds 69% of experimentally reported TFBSs and 85% of the CRMs in a reference data set of regions upstream of genes differentially expressed in skeletal muscle cells. A discriminant procedure based on the Output of the model specifically discriminated regulatory sequences in muscle-specific genes in an independent test set. Application of the method to the analysis of 2710 10-kb fragments upstream of annotated human genes identified 17 novel candidate modules with a false discovery rate less than or equal to0.05, demonstrating the applicability of the method to genome-scale data.
Keywords:
STATISTICAL SIGNIFICANCE
COMPUTATIONAL-DETECTION
GENE
EXPRESSION
PROMOTER
IDENTIFICATION
SEQUENCES
REGIONS
PROTEIN
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Journal

Genome Research cover
Genome Research
IF:
5.5
Papers:
5.6K
Citations:
4.3W

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