{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Rebeiz M"],"funding":["NIGMS NIH HHS"],"pagination":["9888-93"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC125053"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["99(15)"],"pubmed_abstract":["A large fraction of the information content of metazoan genomes resides in the transcriptional and posttranscriptional cis-regulatory elements that collectively provide the blueprint for using the protein-coding capacity of the DNA, thus guiding the development and physiology of the entire organism. As successive whole-genome sequencing projects--including those of mice and humans--are completed, we have full access to the regulatory genome of yet another species. But our ability to decipher the cis-regulatory code, and hence to link genes into regulatory networks on a global scale, is currently very limited. Here we describe SCORE (Site Clustering Over Random Expectation), a computational method for identifying transcriptional cis-regulatory modules based on the fact that they often conta"],"journal":["Proceedings of the National Academy of Sciences of the United States of America"],"pubmed_title":["SCORE: a computational approach to the identification of cis-regulatory modules and target genes in whole-genome sequence data. Site clustering over random expectation."],"pmcid":["PMC125053"],"funding_grant_id":["GM62279","R01 GM046993","R01 GM062279","GM46993"],"pubmed_authors":["Rebeiz M","Reeves NL","Posakony JW"],"additional_accession":[]},"is_claimable":false,"name":"SCORE: a computational approach to the identification of cis-regulatory modules and target genes in whole-genome sequence data. Site clustering over random expectation.","description":"A large fraction of the information content of metazoan genomes resides in the transcriptional and posttranscriptional cis-regulatory elements that collectively provide the blueprint for using the protein-coding capacity of the DNA, thus guiding the development and physiology of the entire organism. As successive whole-genome sequencing projects--including those of mice and humans--are completed, we have full access to the regulatory genome of yet another species. But our ability to decipher the cis-regulatory code, and hence to link genes into regulatory networks on a global scale, is currently very limited. Here we describe SCORE (Site Clustering Over Random Expectation), a computational method for identifying transcriptional cis-regulatory modules based on the fact that they often conta","dates":{"release":"2002-01-01T00:00:00Z","publication":"2002 Jul","modification":"2025-04-21T16:26:07.044Z","creation":"2019-03-27T00:17:14Z"},"accession":"S-EPMC125053","cross_references":{"pubmed":["12107285"],"doi":["10.1073/pnas.152320899"]}}