ABF1/YKL112W Literature Guide Help

Other names published for ABF1: BAF1, OBF1, REB2, SBF1, YKL112W

ABF1 - Computational analysis (43)

Results: 1 - 30 of 43 records
   1  2 
ReferenceOther Genes Addressed
Hansen L, et al.  (2012) Differences in local genomic context of bound and unbound motifs. Gene 506(1):125-34
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
Higa CH, et al.  (2011) Constraint-based analysis of gene interactions using restricted boolean networks and time-series data. BMC Proc 5 Suppl 2():S5
Swamy KB, et al.  (2011) Evidence of association between Nucleosome Occupancy and the Evolution of Transcription Factor Binding Sites in Yeast. BMC Evol Biol 11(1):150
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
Bhaskar A and Keich U  (2010) Confidently estimating the number of DNA replication origins. Stat Appl Genet Mol Biol 9(1):Article28
Chen X, et al.  (2010) A dynamic Bayesian network for identifying protein-binding footprints from single molecule-based sequencing data. Bioinformatics 26(12):i334-42
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
Hu J, et al.  (2010) Analysis of transcriptional synergy between upstream regions and introns in ribosomal protein genes of yeast. Comput Biol Chem 34(2):106-14
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
Tanaka Y, et al.  (2010) Positional variations among heterogeneous nucleosome maps give dynamical information on chromatin. Chromosoma 119(4):391-404
Ay F, et al.  (2009) Scalable steady state analysis of boolean biological regulatory networks. PLoS One 4(12):e7992
Barea F and Bonatto D  (2009) Aging defined by a chronologic-replicative protein network in Saccharomyces cerevisiae: an interactome analysis. Mech Ageing Dev 130(7):444-60
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
Maynou J, et al.  (2009) Transcription factor binding site detection through position cross-mutual information variability analysis. Conf Proc IEEE Eng Med Biol Soc 1():7087-90
Nguyen Ba AN, et al.  (2009) NLStradamus: a simple Hidden Markov Model for nuclear localization signal prediction. BMC Bioinformatics 10:202
Swamy KB, et al.  (2009) Impact of DNA-binding position variants on yeast gene expression. Nucleic Acids Res 37(21):6991-7001
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
Kundaje A, et al.  (2008) A predictive model of the oxygen and heme regulatory network in yeast. PLoS Comput Biol 4(11):e1000224
Schlecht U, et al.  (2008) Genome-wide Expression Profiling, In Vivo DNA Binding Analysis, and Probabilistic Motif Prediction Reveal Novel Abf1 Target Genes during Fermentation, Respiration, and Sporulation in Yeast. Mol Biol Cell 19(5):2193-2207
Chen G, et al.  (2007) Clustering of genes into regulons using integrated modeling-COGRIM. Genome Biol 8(1):R4
Holloway DT, et al.  (2007) Machine learning for regulatory analysis and transcription factor target prediction in yeast. Syst Synth Biol 1(1):25-46
Kinney JB, et al.  (2007) Precise physical models of protein-DNA interaction from high-throughput data. Proc Natl Acad Sci U S A 104(2):501-6
McCord RP, et al.  (2007) Inferring condition-specific transcription factor function from DNA binding and gene expression data. Mol Syst Biol 3():100
Roider HG, et al.  (2007) Predicting transcription factor affinities to DNA from a biophysical model. Bioinformatics 23(2):134-41
Results: 1 - 30 of 43 records
   1  2