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本文引用的文献
1
Dual regulation by pairs of cyclin-dependent protein kinases and histone deacetylases controls G1 transcription in budding yeast.
PLoS Biol. 2009 Sep;7(9):e1000188. doi: 10.1371/journal.pbio.1000188. Epub 2009 Sep 8.
2
Global control of cell-cycle transcription by coupled CDK and network oscillators.
Nature. 2008 Jun 12;453(7197):944-7. doi: 10.1038/nature06955. Epub 2008 May 7.
3
Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data.
BMC Bioinformatics. 2007 Aug 3;8:283. doi: 10.1186/1471-2105-8-283.
4
Clustering of genes into regulons using integrated modeling-COGRIM.
Genome Biol. 2007;8(1):R4. doi: 10.1186/gb-2007-8-1-r4.
5
A Gibbs sampler for the identification of gene expression and network connectivity consistency.
Bioinformatics. 2006 Dec 15;22(24):3040-6. doi: 10.1093/bioinformatics/btl541. Epub 2006 Oct 23.
6
Cluster analysis of protein array results via similarity of Gene Ontology annotation.
BMC Bioinformatics. 2006 Jul 12;7:338. doi: 10.1186/1471-2105-7-338.
7
The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo.
Genome Biol. 2006;7(5):R36. doi: 10.1186/gb-2006-7-5-r36. Epub 2006 May 10.
8
Inferring transcriptional modules from ChIP-chip, motif and microarray data.
Genome Biol. 2006;7(5):R37. doi: 10.1186/gb-2006-7-5-r37. Epub 2006 May 5.
9
Significance analysis of time course microarray experiments.
Proc Natl Acad Sci U S A. 2005 Sep 6;102(36):12837-42. doi: 10.1073/pnas.0504609102. Epub 2005 Sep 2.
10
Transcriptional regulatory code of a eukaryotic genome.
Nature. 2004 Sep 2;431(7004):99-104. doi: 10.1038/nature02800.
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