Identification of self-consistent modulons from bacterial microarray expression data with the help of structured regulon gene sets

Handle URI:
http://hdl.handle.net/10754/564681
Title:
Identification of self-consistent modulons from bacterial microarray expression data with the help of structured regulon gene sets
Authors:
Permina, Elizaveta A.; Medvedeva, Yulia; Baeck, Pia M.; Hegde, Shubhada R.; Mande, Shekhar C.; Makeev, Vsevolod J.
Abstract:
Identification of bacterial modulons from series of gene expression measurements on microarrays is a principal problem, especially relevant for inadequately studied but practically important species. Usage of a priori information on regulatory interactions helps to evaluate parameters for regulatory subnetwork inference. We suggest a procedure for modulon construction where a seed regulon is iteratively updated with genes having expression patterns similar to those for regulon member genes. A set of genes essential for a regulon is used to control modulon updating. Essential genes for a regulon were selected as a subset of regulon genes highly related by different measures to each other. Using Escherichia coli as a model, we studied how modulon identification depends on the data, including the microarray experiments set, the adopted relevance measure and the regulon itself. We have found that results of modulon identification are highly dependent on all parameters studied and thus the resulting modulon varies substantially depending on the identification procedure. Yet, modulons that were identified correctly displayed higher stability during iterations, which allows developing a procedure for reliable modulon identification in the case of less studied species where the known regulatory interactions are sparse. Copyright © 2013 Taylor & Francis.
KAUST Department:
Computational Bioscience Research Center (CBRC)
Publisher:
Informa UK Limited
Journal:
Journal of Biomolecular Structure and Dynamics
Issue Date:
Jan-2013
DOI:
10.1080/07391102.2012.691368
PubMed ID:
22803819
Type:
Article
ISSN:
07391102
Sponsors:
We are grateful to Dmitri Ravcheev for the fruitful consultation and for information provided about PurR regulon and Alexander Favorov for kindly providing a module for calculation of exact Fisher test. This study was partially supported with Russian Fund of Basic Research grant 10-04-92,663-IND-a and Department of Science and Technology, India grant INT/RFBR/P-31.
Appears in Collections:
Articles; Computational Bioscience Research Center (CBRC)

Full metadata record

DC FieldValue Language
dc.contributor.authorPermina, Elizaveta A.en
dc.contributor.authorMedvedeva, Yuliaen
dc.contributor.authorBaeck, Pia M.en
dc.contributor.authorHegde, Shubhada R.en
dc.contributor.authorMande, Shekhar C.en
dc.contributor.authorMakeev, Vsevolod J.en
dc.date.accessioned2015-08-04T07:12:10Zen
dc.date.available2015-08-04T07:12:10Zen
dc.date.issued2013-01en
dc.identifier.issn07391102en
dc.identifier.pmid22803819en
dc.identifier.doi10.1080/07391102.2012.691368en
dc.identifier.urihttp://hdl.handle.net/10754/564681en
dc.description.abstractIdentification of bacterial modulons from series of gene expression measurements on microarrays is a principal problem, especially relevant for inadequately studied but practically important species. Usage of a priori information on regulatory interactions helps to evaluate parameters for regulatory subnetwork inference. We suggest a procedure for modulon construction where a seed regulon is iteratively updated with genes having expression patterns similar to those for regulon member genes. A set of genes essential for a regulon is used to control modulon updating. Essential genes for a regulon were selected as a subset of regulon genes highly related by different measures to each other. Using Escherichia coli as a model, we studied how modulon identification depends on the data, including the microarray experiments set, the adopted relevance measure and the regulon itself. We have found that results of modulon identification are highly dependent on all parameters studied and thus the resulting modulon varies substantially depending on the identification procedure. Yet, modulons that were identified correctly displayed higher stability during iterations, which allows developing a procedure for reliable modulon identification in the case of less studied species where the known regulatory interactions are sparse. Copyright © 2013 Taylor & Francis.en
dc.description.sponsorshipWe are grateful to Dmitri Ravcheev for the fruitful consultation and for information provided about PurR regulon and Alexander Favorov for kindly providing a module for calculation of exact Fisher test. This study was partially supported with Russian Fund of Basic Research grant 10-04-92,663-IND-a and Department of Science and Technology, India grant INT/RFBR/P-31.en
dc.publisherInforma UK Limiteden
dc.subjectData analysisen
dc.subjectHeuristic learningen
dc.subjectMicroarrayen
dc.subjectModulonen
dc.subjectRegulonen
dc.subjectTranscriptional factorsen
dc.titleIdentification of self-consistent modulons from bacterial microarray expression data with the help of structured regulon gene setsen
dc.typeArticleen
dc.contributor.departmentComputational Bioscience Research Center (CBRC)en
dc.identifier.journalJournal of Biomolecular Structure and Dynamicsen
dc.contributor.institutionVavilov Institute of General Genetics, 3 Gubkina str., Moscow GSP-1, 119991, Russian Federationen
dc.contributor.institutionUpper Austria University of Applied Sciences, Softwarepark 11, Hagenberg 4232, Austriaen
dc.contributor.institutionNational Centre for Cell Science, NCCS Complex, Pune University Campus, Ganeshkhind, Pune 411007, Maharashtra, Indiaen
dc.contributor.institutionCentre for DNA Fingerprinting and Diagnostics, Bldg. 7, Nampally, Hyderabad 500 001, Indiaen
dc.contributor.institutionState Research Centre of Genetics, Selection of Industrial Microorganisms, 1-1st Dorozhny proezd, Moscow 117545, Russian Federationen
kaust.authorMedvedeva, Yuliaen

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