Title
cis-Regulatory Element Prediction in Mammalian Genomes
Abstract
The identification of cis-regulatory elements and modules is an important step in understanding the regulation of genes. We have developed a pipeline capable of running multiple motif prediction methods on a whole genome scale. Using gene expression datasets to identify co-expressed genes and the Ensemhl Compara database orthologues, we assemble input sequence sets comprised of the upstream regions of a target gene, its orthologues and co-expressed genes on the premise that such genes will share promoters by evolution (orthologues) or share regulatory control mechanisms (co-expressed genes). Co-expressed genes are identified by an approach that combines Pearson distances from multiple gene expression datasets derived from multiple experimental approaches and calibrated against the GO database. Our pipeline runs a number of established motif detection algorithms with a range of parameter settings on the input dataset. We integrate the diverse result sets by scoring motifs with a method-independent function. For each target gene, we assign p-values to the motif score by running the discovery pipeline on multiple sets of input sequence containing the target gene, non-coexpressed genes and "Jake" orthologues generated by neutral numerical evolution. We have predicted 30,636 motif binding sites in human for 4,182 genes and an initial set of 472 motif binding sites in mouse for 92 genes with p<0.001. The positive predictive value against a library of biologically confirmed regulatory sites approaches 0.4 at the highest p-value threshold. Predicted regulatory elements and other resources from the project are available at www.cisred.org.
Year
DOI
Venue
2005
10.1109/CSBW.2005.35
CSB Workshops
Keywords
Field
DocType
genetics
Genome,Promoter,Gene,Cis-regulatory element,Biology,Sequence motif,Gene prediction,Gene expression,Motif (music),Bioinformatics
Conference
ISBN
Citations 
PageRank 
0-7695-2442-7
0
0.34
References 
Authors
4
16
Name
Order
Citations
PageRank
Asim Siddiqui171.44
Gordon Robertson212015.23
M Bilenky3252.89
Tamara Astakhova4253.23
Obi L. Griffith520717.69
M Hassel6252.89
Keven Lin700.34
Stephen B Montgomery89710.31
Mehrdad Oveisi900.34
E D Pleasance10536.40
Neil Robertson1100.68
Monica C. Sleumer1212911.54
K Teague13252.89
Richard Varhol1410613.43
Maggie Zhang1500.34
Steven J. M. Jones1657871.55