title: Regulatory element detection using correlation with expression.
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.
authors.affiliation: Center for Studies in Physics and Biology, The Rockefeller University, New York, New York, USA. bussemaker@bio.uva.nl
authors.forename: H J
authors.initials: HJ
authors.lastname: Bussemaker
authors.forename: H
authors.initials: H
authors.lastname: Li
authors.forename: E D
authors.initials: ED
authors.lastname: Siggia
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D002453:Cell Cycle / Q000235:genetics; D016384:Consensus Sequence; D004268:DNA-Binding Proteins / Q000378:metabolism; D015966:Gene Expression Regulation, Fungal; D026341:Minichromosome Maintenance 1 Protein; D008962:Models, Theoretical; D012045:Regulatory Sequences, Nucleic Acid; D012441:Saccharomyces cerevisiae / Q000166:cytology / Q000235:genetics*; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D004268:DNA-Binding Proteins; D026341:Minichromosome Maintenance 1 Protein; D014157:Transcription Factors