318 related articles for article (PubMed ID: 24565265)
1. Inferring functional transcription factor-gene binding pairs by integrating transcription factor binding data with transcription factor knockout data.
Yang TH; Wu WS
BMC Syst Biol; 2013; 7 Suppl 6(Suppl 6):S13. PubMed ID: 24565265
[TBL] [Abstract][Full Text] [Related]
2. Identifying biologically interpretable transcription factor knockout targets by jointly analyzing the transcription factor knockout microarray and the ChIP-chip data.
Yang TH; Wu WS
BMC Syst Biol; 2012 Aug; 6():102. PubMed ID: 22898448
[TBL] [Abstract][Full Text] [Related]
3. Properly defining the targets of a transcription factor significantly improves the computational identification of cooperative transcription factor pairs in yeast.
Wu WS; Lai FJ
BMC Genomics; 2015; 16 Suppl 12(Suppl 12):S10. PubMed ID: 26679776
[TBL] [Abstract][Full Text] [Related]
4. Transcription factor regulatory modules provide the molecular mechanisms for functional redundancy observed among transcription factors in yeast.
Yang TH
BMC Bioinformatics; 2019 Dec; 20(Suppl 23):630. PubMed ID: 31881824
[TBL] [Abstract][Full Text] [Related]
5. A biophysical model for analysis of transcription factor interaction and binding site arrangement from genome-wide binding data.
He X; Chen CC; Hong F; Fang F; Sinha S; Ng HH; Zhong S
PLoS One; 2009 Dec; 4(12):e8155. PubMed ID: 19956545
[TBL] [Abstract][Full Text] [Related]
6. Identifying cooperative transcription factors in yeast using multiple data sources.
Lai FJ; Jhu MH; Chiu CC; Huang YM; Wu WS
BMC Syst Biol; 2014; 8 Suppl 5(Suppl 5):S2. PubMed ID: 25559499
[TBL] [Abstract][Full Text] [Related]
7. A graphical model approach visualizes regulatory relationships between genome-wide transcription factor binding profiles.
Ng FSL; Ruau D; Wernisch L; Göttgens B
Brief Bioinform; 2018 Jan; 19(1):162-173. PubMed ID: 27780826
[TBL] [Abstract][Full Text] [Related]
8. An improved ChIP-seq peak detection system for simultaneously identifying post-translational modified transcription factors by combinatorial fusion, using SUMOylation as an example.
Cheng CY; Chu CH; Hsu HW; Hsu FR; Tang CY; Wang WC; Kung HJ; Chang PC
BMC Genomics; 2014; 15 Suppl 1(Suppl 1):S1. PubMed ID: 24564277
[TBL] [Abstract][Full Text] [Related]
9. Revealing transcription factor and histone modification co-localization and dynamics across cell lines by integrating ChIP-seq and RNA-seq data.
Zhang L; Xue G; Liu J; Li Q; Wang Y
BMC Genomics; 2018 Dec; 19(Suppl 10):914. PubMed ID: 30598100
[TBL] [Abstract][Full Text] [Related]
10. Functional redundancy of transcription factors explains why most binding targets of a transcription factor are not affected when the transcription factor is knocked out.
Wu WS; Lai FJ
BMC Syst Biol; 2015; 9 Suppl 6(Suppl 6):S2. PubMed ID: 26678747
[TBL] [Abstract][Full Text] [Related]
11. ChIPXpress: using publicly available gene expression data to improve ChIP-seq and ChIP-chip target gene ranking.
Wu G; Ji H
BMC Bioinformatics; 2013 Jun; 14():188. PubMed ID: 23758851
[TBL] [Abstract][Full Text] [Related]
12. The Role of Genome Accessibility in Transcription Factor Binding in Bacteria.
Gomes AL; Wang HH
PLoS Comput Biol; 2016 Apr; 12(4):e1004891. PubMed ID: 27104615
[TBL] [Abstract][Full Text] [Related]
13. Transcription factor-binding k-mer analysis clarifies the cell type dependency of binding specificities and cis-regulatory SNPs in humans.
Tahara S; Tsuchiya T; Matsumoto H; Ozaki H
BMC Genomics; 2023 Oct; 24(1):597. PubMed ID: 37805453
[TBL] [Abstract][Full Text] [Related]
14. An efficient method to transcription factor binding sites imputation via simultaneous completion of multiple matrices with positional consistency.
Guo WL; Huang DS
Mol Biosyst; 2017 Aug; 13(9):1827-1837. PubMed ID: 28718849
[TBL] [Abstract][Full Text] [Related]
15. Inferring condition-specific targets of human TF-TF complexes using ChIP-seq data.
Yang CC; Chen MH; Lin SY; Andrews EH; Cheng C; Liu CC; Chen JJ
BMC Genomics; 2017 Jan; 18(1):61. PubMed ID: 28068916
[TBL] [Abstract][Full Text] [Related]
16. ChIP-GSM: Inferring active transcription factor modules to predict functional regulatory elements.
Chen X; Neuwald AF; Hilakivi-Clarke L; Clarke R; Xuan J
PLoS Comput Biol; 2021 Jul; 17(7):e1009203. PubMed ID: 34292930
[TBL] [Abstract][Full Text] [Related]
17. Systematic identification of yeast cell cycle transcription factors using multiple data sources.
Wu WS; Li WH
BMC Bioinformatics; 2008 Dec; 9():522. PubMed ID: 19061501
[TBL] [Abstract][Full Text] [Related]
18. Coherent functional modules improve transcription factor target identification, cooperativity prediction, and disease association.
Karczewski KJ; Snyder M; Altman RB; Tatonetti NP
PLoS Genet; 2014 Feb; 10(2):e1004122. PubMed ID: 24516403
[TBL] [Abstract][Full Text] [Related]
19. Probing transcription factor combinatorics in different promoter classes and in enhancers.
Vandel J; Cassan O; Lèbre S; Lecellier CH; Bréhélin L
BMC Genomics; 2019 Feb; 20(1):103. PubMed ID: 30709337
[TBL] [Abstract][Full Text] [Related]
20. hTFtarget: A Comprehensive Database for Regulations of Human Transcription Factors and Their Targets.
Zhang Q; Liu W; Zhang HM; Xie GY; Miao YR; Xia M; Guo AY
Genomics Proteomics Bioinformatics; 2020 Apr; 18(2):120-128. PubMed ID: 32858223
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]