Conference Paper: Growing gene network by integration of gene expression, motif sequence and metabolic information

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TitleGrowing gene network by integration of gene expression, motif sequence and metabolic information
AuthorsGeng, B1 2
Zhou, X1
Hung, YS2
Wong, S1
KeywordsGene Expression
Gene Network Growing
Metabolic Reaction
Motif Sequence
Issue Date2007
CitationAip Conference Proceedings, 2007, v. 952, p. 279-286 [How to Cite?]
DOI: http://dx.doi.org/10.1063/1.2816632
AbstractIn computational biology, gene networks are typically inferred from gene expression data alone. Incorporating multiple types of biological information makes it possible to improve gene network estimation. In this paper, we describe an approach for growing gene network from a sub-network by the integration of gene expression data, motif sequence, and metabolic information. To evaluate the approach, we apply it to a pool of E.coli genes related to aspartate pathway. The results show that integrative approach has potentials of reconstructing more accurate gene networks. © 2007 American Institute of Physics.
ISSN0094-243X
2011 SCImago Journal Rankings: 0.033
DOIhttp://dx.doi.org/10.1063/1.2816632
ReferencesReferences in Scopus
DC Field
Value
dc.contributor.authorGeng, B
dc.contributor.authorZhou, X
dc.contributor.authorHung, YS
dc.contributor.authorWong, S
dc.date.accessioned2012-08-08T09:00:27Z
dc.date.available2012-08-08T09:00:27Z
dc.date.issued2007
dc.description.abstractIn computational biology, gene networks are typically inferred from gene expression data alone. Incorporating multiple types of biological information makes it possible to improve gene network estimation. In this paper, we describe an approach for growing gene network from a sub-network by the integration of gene expression data, motif sequence, and metabolic information. To evaluate the approach, we apply it to a pool of E.coli genes related to aspartate pathway. The results show that integrative approach has potentials of reconstructing more accurate gene networks. © 2007 American Institute of Physics.
dc.description.natureLink_to_subscribed_fulltext
dc.identifier.citationAip Conference Proceedings, 2007, v. 952, p. 279-286 [How to Cite?]
DOI: http://dx.doi.org/10.1063/1.2816632
dc.identifier.doihttp://dx.doi.org/10.1063/1.2816632
dc.identifier.epage286
dc.identifier.issn0094-243X
2011 SCImago Journal Rankings: 0.033
dc.identifier.scopuseid_2-s2.0-71449108721
dc.identifier.spage279
dc.identifier.urihttp://hdl.handle.net/10722/158606
dc.identifier.volume952
dc.languageeng
dc.publisher.placeUnited States
dc.relation.ispartofAIP Conference Proceedings
dc.relation.referencesReferences in Scopus
dc.subjectGene Expression
dc.subjectGene Network Growing
dc.subjectMetabolic Reaction
dc.subjectMotif Sequence
dc.titleGrowing gene network by integration of gene expression, motif sequence and metabolic information
dc.typeConference_Paper
Author Affiliations
  1. Cornell University
  2. The University of Hong Kong