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dc.contributor.authorCharaniya, Salim P.en_US
dc.contributor.authorJayapal, Karthik P.en_US
dc.contributor.authorMehra, Sarikaen_US
dc.contributor.authorLian, Weien_US
dc.contributor.authorSherman, David H.en_US
dc.contributor.authorHu, Wei-Shouen_US
dc.date.accessioned2006-09-11T19:35:15Z
dc.date.available2006-09-11T19:35:15Z
dc.date.issued2006-02en_US
dc.identifier.citationMehra, Sarika; Lian, Wei; Jayapal, Karthik P.; Charaniya, Salim P.; Sherman, David H.; Hu, Wei-Shou; (2006). "A framework to analyze multiple time series data: A case study with Streptomyces coelicolor ." Journal of Industrial Microbiology & Biotechnology 33(2): 159-172. <http://hdl.handle.net/2027.42/47950>en_US
dc.identifier.issn1476-5535en_US
dc.identifier.issn1367-5435en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/47950
dc.identifier.urihttp://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=16217633&dopt=citationen_US
dc.description.abstractTranscriptional regulation in differentiating microorganisms is highly dynamic involving multiple and interwinding circuits consisted of many regulatory genes. Elucidation of these networks may provide the key to harness the full capacity of many organisms that produce natural products. A powerful tool evolved in the past decade is global transcriptional study of mutants in which one or more key regulatory genes of interest have been deleted. To study regulatory mutants of Streptomyces coelicolor , we developed a framework of systematic analysis of gene expression dynamics. Instead of pair-wise comparison of samples in different combinations, genomic DNA was used as a common reference for all samples in microarray assays, thus, enabling direct comparison of gene transcription dynamics across different isogenic mutants. As growth and various differentiation events may unfold at different rates in different mutants, the global transcription profiles of each mutant were first aligned computationally to those of the wild type, with respect to the corresponding growth and differentiation stages, prior to identification of kinetically differentially expressed genes. The genome scale transcriptome data from wild type and a Δ absA1 mutant of Streptomyces coelicolor were analyzed within this framework, and the regulatory elements affected by the gene knockout were identified. This methodology should find general applications in the analysis of other mutants in our repertoire and in other biological systems.en_US
dc.format.extent804640 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherSpringer-Verlag; Society for Industrial Microbiologyen_US
dc.subject.otherTime Seriesen_US
dc.subject.otherStreptomycesen_US
dc.subject.otherAntibioticsen_US
dc.subject.otherDNA Microarrayen_US
dc.subject.otherTranscriptome Analysisen_US
dc.titleA framework to analyze multiple time series data: A case study with Streptomyces coelicoloren_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelBiomedical Engineeringen_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumLife Sciences Institute, and Departments of Medicinal Chemistry, Chemistry, Microbiology & Immunology, University of Michigan, 210 Washtenaw Avenue, Ann Arbor, MI, 48109-2216, USA,en_US
dc.contributor.affiliationotherDepartment of Chemical Engineering and Materials Science, University of Minnesota, 421 Washington Avenue SE, Minneapolis, MN, 55455-0132, USA,en_US
dc.contributor.affiliationotherDepartment of Chemical Engineering and Materials Science, University of Minnesota, 421 Washington Avenue SE, Minneapolis, MN, 55455-0132, USA,en_US
dc.contributor.affiliationotherDepartment of Chemical Engineering and Materials Science, University of Minnesota, 421 Washington Avenue SE, Minneapolis, MN, 55455-0132, USA,en_US
dc.contributor.affiliationotherDepartment of Chemical Engineering and Materials Science, University of Minnesota, 421 Washington Avenue SE, Minneapolis, MN, 55455-0132, USA,en_US
dc.contributor.affiliationotherDepartment of Chemical Engineering and Materials Science, University of Minnesota, 421 Washington Avenue SE, Minneapolis, MN, 55455-0132, USA,en_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.identifier.pmid16217633en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/47950/1/10295_2005_Article_34.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1007/s10295-005-0034-7en_US
dc.identifier.sourceJournal of Industrial Microbiology & Biotechnologyen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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