195 related articles for article (PubMed ID: 19661283)
1. Predicting eukaryotic transcriptional cooperativity by Bayesian network integration of genome-wide data.
Wang Y; Zhang XS; Xia Y
Nucleic Acids Res; 2009 Oct; 37(18):5943-58. PubMed ID: 19661283
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. Identifying cooperativity among transcription factors controlling the cell cycle in yeast.
Banerjee N; Zhang MQ
Nucleic Acids Res; 2003 Dec; 31(23):7024-31. PubMed ID: 14627835
[TBL] [Abstract][Full Text] [Related]
4. A Bayesian data fusion based approach for learning genome-wide transcriptional regulatory networks.
Sauta E; Demartini A; Vitali F; Riva A; Bellazzi R
BMC Bioinformatics; 2020 May; 21(1):219. PubMed ID: 32471360
[TBL] [Abstract][Full Text] [Related]
5. Topological comparison of methods for predicting transcriptional cooperativity in yeast.
Aguilar D; Oliva B
BMC Genomics; 2008 Mar; 9():137. PubMed ID: 18366726
[TBL] [Abstract][Full Text] [Related]
6. Integrating multiple resources to identify specific transcriptional cooperativity with a Bayesian approach.
Hu P; Shen Z; Tu H; Zhang L; Shi T
Bioinformatics; 2014 Mar; 30(6):823-30. PubMed ID: 24192543
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. A comprehensive performance evaluation on the prediction results of existing cooperative transcription factors identification algorithms.
Lai FJ; Chang HT; Huang YM; Wu WS
BMC Syst Biol; 2014; 8 Suppl 4(Suppl 4):S9. PubMed ID: 25521604
[TBL] [Abstract][Full Text] [Related]
9. Transcriptional network inference from functional similarity and expression data: a global supervised approach.
Ambroise J; Robert A; Macq B; Gala JL
Stat Appl Genet Mol Biol; 2012 Jan; 11(1):Article 2. PubMed ID: 22499684
[TBL] [Abstract][Full Text] [Related]
10. Integrating genomic data to predict transcription factor binding.
Holloway DT; Kon M; DeLisi C
Genome Inform; 2005; 16(1):83-94. PubMed ID: 16362910
[TBL] [Abstract][Full Text] [Related]
11. Integrating large-scale functional genomic data to dissect the complexity of yeast regulatory networks.
Zhu J; Zhang B; Smith EN; Drees B; Brem RB; Kruglyak L; Bumgarner RE; Schadt EE
Nat Genet; 2008 Jul; 40(7):854-61. PubMed ID: 18552845
[TBL] [Abstract][Full Text] [Related]
12. Classifying transcription factor targets and discovering relevant biological features.
Holloway DT; Kon M; DeLisi C
Biol Direct; 2008 May; 3():22. PubMed ID: 18513408
[TBL] [Abstract][Full Text] [Related]
13. A Bayesian network driven approach to model the transcriptional response to nitric oxide in Saccharomyces cerevisiae.
Zhu J; Jambhekar A; Sarver A; DeRisi J
PLoS One; 2006 Dec; 1(1):e94. PubMed ID: 17183726
[TBL] [Abstract][Full Text] [Related]
14. Inferring condition-specific modulation of transcription factor activity in yeast through regulon-based analysis of genomewide expression.
Boorsma A; Lu XJ; Zakrzewska A; Klis FM; Bussemaker HJ
PLoS One; 2008 Sep; 3(9):e3112. PubMed ID: 18769540
[TBL] [Abstract][Full Text] [Related]
15. Improved recovery of cell-cycle gene expression in Saccharomyces cerevisiae from regulatory interactions in multiple omics data.
Panchy NL; Lloyd JP; Shiu SH
BMC Genomics; 2020 Feb; 21(1):159. PubMed ID: 32054475
[TBL] [Abstract][Full Text] [Related]
16. Identification of transcription factor cooperativity via stochastic system model.
Chang YH; Wang YC; Chen BS
Bioinformatics; 2006 Sep; 22(18):2276-82. PubMed ID: 16844711
[TBL] [Abstract][Full Text] [Related]
17. A synthetic biology framework for programming eukaryotic transcription functions.
Khalil AS; Lu TK; Bashor CJ; Ramirez CL; Pyenson NC; Joung JK; Collins JJ
Cell; 2012 Aug; 150(3):647-58. PubMed ID: 22863014
[TBL] [Abstract][Full Text] [Related]
18. Genomic analysis reveals a tight link between transcription factor dynamics and regulatory network architecture.
Jothi R; Balaji S; Wuster A; Grochow JA; Gsponer J; Przytycka TM; Aravind L; Babu MM
Mol Syst Biol; 2009; 5():294. PubMed ID: 19690563
[TBL] [Abstract][Full Text] [Related]
19. De-novo learning of genome-scale regulatory networks in S. cerevisiae.
Ma S; Kemmeren P; Gresham D; Statnikov A
PLoS One; 2014; 9(9):e106479. PubMed ID: 25215507
[TBL] [Abstract][Full Text] [Related]
20. Detecting Cooperativity between Transcription Factors Based on Functional Coherence and Similarity of Their Target Gene Sets.
Wu WS; Lai FJ
PLoS One; 2016; 11(9):e0162931. PubMed ID: 27623007
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
