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Article: Assessing clusters and motifs from gene expression data

TitleAssessing clusters and motifs from gene expression data
Authors
Issue Date2001
PublisherCold Spring Harbor Laboratory Press, Publications Department. The Journal's web site is located at http://www.genome.org
Citation
Genome Research, 2001, v. 11 n. 1, p. 112-123 How to Cite?
AbstractLarge-scale gene expression studies and genomic sequencing projects are providing vast amounts of information that can be used to identify or predict cellular regulatory processes. Genes can be clustered on the basis of the similarity of their expression profiles or function and these clusters are likely to contain genes that are regulated by the same transcription factors. Searches for cis-regulatory elements can then be undertaken in the noncoding regions of the clustered genes. However, it is necessary to assess the efficiency of both the gene clustering and the postulated regulatory motifs, as there are many difficulties associated with clustering and determining the functional relevance of matches to sequence motifs. We have developed a method to assess the potential functional significance of clusters and motifs based on the probability of finding a certain number of matches to a motif in all of the gene clusters. To avoid problems with threshold scores for a match, the top matches to a motif are taken in several sample sizes. Genes from a sample are then counted by the cluster in which they appear. The probability of observing these counts by chance is calculated using the hypergeometric distribution. Because of the multiple sample sizes, strong and weak matching motifs can be detected and refined and significant matches to motifs across cluster boundaries are observed as all clusters are considered. By applying this method to many motifs and to a cluster set of yeast genes, we detected a similarity between Swi Five Factor and forkhead proteins and suggest that the currently unidentified Swi Five Factor is one of the yeast forkhead proteins.
Persistent Identifierhttp://hdl.handle.net/10722/68302
ISSN
2015 Impact Factor: 11.351
2015 SCImago Journal Rankings: 14.352
PubMed Central ID
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorJakt, LMen_HK
dc.contributor.authorCao, Len_HK
dc.contributor.authorCheah, KSEen_HK
dc.contributor.authorSmith, DKen_HK
dc.date.accessioned2010-09-06T06:03:17Z-
dc.date.available2010-09-06T06:03:17Z-
dc.date.issued2001en_HK
dc.identifier.citationGenome Research, 2001, v. 11 n. 1, p. 112-123en_HK
dc.identifier.issn1088-9051en_HK
dc.identifier.urihttp://hdl.handle.net/10722/68302-
dc.description.abstractLarge-scale gene expression studies and genomic sequencing projects are providing vast amounts of information that can be used to identify or predict cellular regulatory processes. Genes can be clustered on the basis of the similarity of their expression profiles or function and these clusters are likely to contain genes that are regulated by the same transcription factors. Searches for cis-regulatory elements can then be undertaken in the noncoding regions of the clustered genes. However, it is necessary to assess the efficiency of both the gene clustering and the postulated regulatory motifs, as there are many difficulties associated with clustering and determining the functional relevance of matches to sequence motifs. We have developed a method to assess the potential functional significance of clusters and motifs based on the probability of finding a certain number of matches to a motif in all of the gene clusters. To avoid problems with threshold scores for a match, the top matches to a motif are taken in several sample sizes. Genes from a sample are then counted by the cluster in which they appear. The probability of observing these counts by chance is calculated using the hypergeometric distribution. Because of the multiple sample sizes, strong and weak matching motifs can be detected and refined and significant matches to motifs across cluster boundaries are observed as all clusters are considered. By applying this method to many motifs and to a cluster set of yeast genes, we detected a similarity between Swi Five Factor and forkhead proteins and suggest that the currently unidentified Swi Five Factor is one of the yeast forkhead proteins.en_HK
dc.languageengen_HK
dc.publisherCold Spring Harbor Laboratory Press, Publications Department. The Journal's web site is located at http://www.genome.orgen_HK
dc.relation.ispartofGenome Researchen_HK
dc.subject.meshAmino Acid Motifs - geneticsen_HK
dc.subject.meshAnimalsen_HK
dc.subject.meshCell Cycle - geneticsen_HK
dc.subject.meshComputational Biology - methodsen_HK
dc.subject.meshDatabases, Factualen_HK
dc.subject.meshDrosophila melanogaster - geneticsen_HK
dc.subject.meshForkhead Transcription Factorsen_HK
dc.subject.meshGene Expression Profiling - methodsen_HK
dc.subject.meshHelix-Loop-Helix Motifs - geneticsen_HK
dc.subject.meshHumansen_HK
dc.subject.meshMiceen_HK
dc.subject.meshMultigene Family - geneticsen_HK
dc.subject.meshNuclear Proteins - geneticsen_HK
dc.subject.meshRatsen_HK
dc.subject.meshSaccharomyces cerevisiae - cytology - geneticsen_HK
dc.subject.meshTranscription Factors - geneticsen_HK
dc.subject.meshXenopus laevis - geneticsen_HK
dc.titleAssessing clusters and motifs from gene expression dataen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1088-9051&volume=11&spage=112&epage=123&date=2001&atitle=Assessing+clusters+and+motifs+from+gene+expression+dataen_HK
dc.identifier.emailCheah, KSE:hrmbdkc@hku.hken_HK
dc.identifier.authorityCheah, KSE=rp00342en_HK
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1101/gr.148301en_HK
dc.identifier.pmid11156620-
dc.identifier.pmcidPMC311053-
dc.identifier.scopuseid_2-s2.0-0035156258en_HK
dc.identifier.hkuros58491en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0035156258&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume11en_HK
dc.identifier.issue1en_HK
dc.identifier.spage112en_HK
dc.identifier.epage123en_HK
dc.identifier.isiWOS:000166361700011-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridJakt, LM=6507406360en_HK
dc.identifier.scopusauthoridCao, L=7401637818en_HK
dc.identifier.scopusauthoridCheah, KSE=35387746200en_HK
dc.identifier.scopusauthoridSmith, DK=7410351143en_HK
dc.identifier.citeulike2931199-

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