Other names published for FKH1: YIL131C
FKH1 LITERATURE TOPICS
- Curated Literature
- Genetics/Cell Biology
- Nucleic Acid Information
- Gene Product Information
- Related Genes/Proteins
- Research Aids
- Genome-wide Analysis
- Proteome-wide Analysis
- Other Topics
- Additional Information
FKH1 - Computational analysis (40)
| Reference | Other Genes Addressed |
|---|---|
| Fernandez MA, et al. (2012) Identification of a core set of signature cell cycle genes whose relative order of time to peak expression is conserved across species. Nucleic Acids Res 40(7):2823-32 | |
| Contador CA, et al. (2011) Identification of transcription factors perturbed by the synthesis of high levels of a foreign protein in yeast saccharomyces cerevisiae. Biotechnol Prog 27(4):925-36 | |
| Erb I and van Nimwegen E (2011) Transcription factor binding site positioning in yeast: proximal promoter motifs characterize tata-less promoters. PLoS One 6(9):e24279 | |
| Gordan R, et al. (2011) Curated collection of yeast transcription factor DNA binding specificity data reveals novel structural and gene regulatory insights. Genome Biol 12(12):R125 | |
| Vohradska E and Vohradsky J (2011) Virtual mutagenesis of the yeast cyclins genetic network reveals complex dynamics of transcriptional control networks. PLoS One 6(4):e18827 | |
| Wang H, et al. (2011) Yeast cell cycle transcription factors identification by variable selection criteria. Gene 485(2):172-6 | |
| Babbitt GA (2010) Relaxed selection against accidental binding of transcription factors with conserved chromatin contexts. Gene 466(1-2):43-8 | |
| Goh WS, et al. (2010) Blurring of high-resolution data shows that the effect of intrinsic nucleosome occupancy on transcription factor binding is mostly regional, not local. PLoS Comput Biol 6(1):e1000649 | |
| Lee E and Bussemaker HJ (2010) Identifying the genetic determinants of transcription factor activity. Mol Syst Biol 6():412 | |
| On T, et al. (2010) The evolutionary landscape of the chromatin modification machinery reveals lineage specific gains, expansions, and losses. Proteins 78(9):2075-89 | |
| To CC and Vohradsky J (2010) Measurement variation determines the gene network topology reconstructed from experimental data: a case study of the yeast cyclin network. FASEB J 24(9):3468-78 | |
| Chen T and Li F (2009) Identifying cell cycle regulators and combinatorial interactions among transcription factors with microarray data and ChIP-chip data. Int J Bioinform Res Appl 5(6):625-46 | |
| Gordan R, et al. (2009) Distinguishing direct versus indirect transcription factor-DNA interactions. Genome Res 19(11):2090-100 | |
| Jothi R, et al. (2009) Genomic analysis reveals a tight link between transcription factor dynamics and regulatory network architecture. Mol Syst Biol 5:294 | |
| Li A and Tuck D (2009) An effective tri-clustering algorithm combining expression data with gene regulation information. Gene Regul Syst Bio 3:49-64 | |
| Swamy KB, et al. (2009) Impact of DNA-binding position variants on yeast gene expression. Nucleic Acids Res 37(21):6991-7001 | |
| Wang Y, et al. (2009) Predicting eukaryotic transcriptional cooperativity by Bayesian network integration of genome-wide data. Nucleic Acids Res 37(18):5943-58 | |
| Xiao Y and Segal MR (2009) Identification of yeast transcriptional regulation networks using multivariate random forests. PLoS Comput Biol 5(6):e1000414 | |
| Ye C, et al. (2009) Using network component analysis to dissect regulatory networks mediated by transcription factors in yeast. PLoS Comput Biol 5(3):e1000311 | |
| Jonnalagadda S and Srinivasan R (2008) Principal components analysis based methodology to identify differentially expressed genes in time-course microarray data. BMC Bioinformatics 9:267 | |
| Lu CC, et al. (2008) Extracting transcription factor binding sites from unaligned gene sequences with statistical models. BMC Bioinformatics 9 Suppl 12:S7 | |
| Ward LD and Bussemaker HJ (2008) Predicting functional transcription factor binding through alignment-free and affinity-based analysis of orthologous promoter sequences. Bioinformatics 24(13):i165-71 | |
| Wu WS and Li WH (2008) Systematic identification of yeast cell cycle transcription factors using multiple data sources. BMC Bioinformatics 9:522 | |
| Chen G, et al. (2007) Clustering of genes into regulons using integrated modeling-COGRIM. Genome Biol 8(1):R4 | |
| Lu Y, et al. (2007) Combined analysis reveals a core set of cycling genes. Genome Biol 8(7):R146 | |
| Morozov AV and Siggia ED (2007) Connecting protein structure with predictions of regulatory sites. Proc Natl Acad Sci U S A 104(17):7068-73 | |
| Cheng C, et al. (2006) MARD: a new method to detect differential gene expression in treatment-control time courses. Bioinformatics 22(21):2650-7 | |
| Galbraith SJ, et al. (2006) Transcriptome network component analysis with limited microarray data. Bioinformatics 22(15):1886-94 | |
| Hart CE, et al. (2006) Connectivity in the yeast cell cycle transcription network: inferences from neural networks. PLoS Comput Biol 2(12):e169 | |
| Wu WS, et al. (2006) Computational reconstruction of transcriptional regulatory modules of the yeast cell cycle. BMC Bioinformatics 7(1):421 |



