Regulatory element detection using correlation with expression View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2001-02

AUTHORS

Harmen J. Bussemaker, Hao Li, Eric D. Siggia

ABSTRACT

We present here a new computational method for discovering cis-regulatory elements that circumvents the need to cluster genes based on their expression profiles. Based on a model in which upstream motifs contribute additively to the log-expression level of a gene, this method requires a single genome-wide set of expression ratios and the upstream sequence for each gene, and outputs statistically significant motifs. Analysis of publicly available expression data for Saccharomyces cerevisiae reveals several new putative regulatory elements, some of which plausibly control the early, transient induction of genes during sporulation. Known motifs generally have high statistical significance. More... »

PAGES

ng0201_167

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/84792

DOI

http://dx.doi.org/10.1038/84792

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1017237252

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/11175784


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