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Towards reconstruction of gene networks from expression data by supervised learning.
Soinov LA, Krestyaninova MA, Brazma A.
Genome Biol. 2003;4(1):R6. Epub 2003 Jan 6.PMID: 12540298 [PubMed - indexed for MEDLINE]Related articlesFree article
A novel model-free approach for reconstruction of time-delayed gene regulatory networks.
Jiang W, Li X, Guo Z, Li C, Wang L, Rao S.
Sci China C Life Sci. 2006 Apr;49(2):190-200.PMID: 16704123 [PubMed - indexed for MEDLINE]Related articles
An ensemble learning approach to reverse-engineering transcriptional regulatory networks from time-series gene expression data.
Ruan J, Deng Y, Perkins EJ, Zhang W.
BMC Genomics. 2009 Jul 7;10 Suppl 1:S8.PMID: 19594885 [PubMed - indexed for MEDLINE]Related articlesFree article
A copula method for modeling directional dependence of genes.
Kim JM, Jung YS, Sungur EA, Han KH, Park C, Sohn I.
BMC Bioinformatics. 2008 May 1;9:225.PMID: 18447957 [PubMed - indexed for MEDLINE]Related articlesFree article
A classification-based framework for predicting and analyzing gene regulatory response.
Kundaje A, Middendorf M, Shah M, Wiggins CH, Freund Y, Leslie C.
BMC Bioinformatics. 2006 Mar 20;7 Suppl 1:S5.PMID: 16723008 [PubMed - indexed for MEDLINE]Related articlesFree article
Reconstructing genetic networks from time ordered gene expression data using Bayesian method with global search algorithm.
Wang SC.
J Bioinform Comput Biol. 2004 Sep;2(3):441-58.PMID: 15359420 [PubMed - indexed for MEDLINE]Related articles
A new dynamic Bayesian network (DBN) approach for identifying gene regulatory networks from time course microarray data.
Zou M, Conzen SD.
Bioinformatics. 2005 Jan 1;21(1):71-9. Epub 2004 Aug 12.PMID: 15308537 [PubMed - indexed for MEDLINE]Related articlesFree article
Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory.
Luo F, Yang Y, Zhong J, Gao H, Khan L, Thompson DK, Zhou J.
BMC Bioinformatics. 2007 Aug 14;8:299.PMID: 17697349 [PubMed - indexed for MEDLINE]Related articlesFree article
A bi-dimensional regression tree approach to the modeling of gene expression regulation.
Ruan J, Zhang W.
Bioinformatics. 2006 Feb 1;22(3):332-40. Epub 2005 Nov 22.PMID: 16303796 [PubMed - indexed for MEDLINE]Related articlesFree article
Computational reconstruction of transcriptional regulatory modules of the yeast cell cycle.
Wu WS, Li WH, Chen BS.
BMC Bioinformatics. 2006 Sep 29;7:421.PMID: 17010188 [PubMed - indexed for MEDLINE]Related articlesFree article
Quantitative characterization of the transcriptional regulatory network in the yeast cell cycle.
Chen HC, Lee HC, Lin TY, Li WH, Chen BS.
Bioinformatics. 2004 Aug 12;20(12):1914-27. Epub 2004 Mar 25.PMID: 15044243 [PubMed - indexed for MEDLINE]Related articlesFree article
Knowledge-assisted recognition of cluster boundaries in gene expression data.
Okada Y, Sahara T, Mitsubayashi H, Ohgiya S, Nagashima T.
Artif Intell Med. 2005 Sep-Oct;35(1-2):171-83.PMID: 16054350 [PubMed - indexed for MEDLINE]Related articles
Supervised classification for gene network reconstruction.
Soinov LA.
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Unraveling condition specific gene transcriptional regulatory networks in Saccharomyces cerevisiae.
Kim H, Hu W, Kluger Y.
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A hybrid Bayesian network learning method for constructing gene networks.
Wang M, Chen Z, Cloutier S.
Comput Biol Chem. 2007 Oct;31(5-6):361-72. Epub 2007 Aug 19.PMID: 17889617 [PubMed - indexed for MEDLINE]Related articles
Inferring adaptive regulation thresholds and association rules from gene expression data through combinatorial optimization learning.
Ponzoni I, Azuaje F, Augusto J, Glass D.
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Clustering of gene expression data using a local shape-based similarity measure.
Balasubramaniyan R, Hüllermeier E, Weskamp N, Kämper J.
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Bayesian Orthogonal Least Squares (BOLS) algorithm for reverse engineering of gene regulatory networks.
Kim CS.
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Gene networks reconstruction and time-series prediction from microarray data using recurrent neural fuzzy networks.
Maraziotis IA, Dragomir A, Bezerianos A.
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Defining transcriptional networks through integrative modeling of mRNA expression and transcription factor binding data.
Gao F, Foat BC, Bussemaker HJ.
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