GAL10/YBR019C Literature Guide Help

Other names published for GAL10: bifunctional UDP-glucose 4-epimerase/aldose 1-epimerase, YBR019C

GAL10 - Computational analysis (20)

ReferenceOther Genes Addressed
Kim KH and Sauro HM  (2012) Adjusting phenotypes by noise control. PLoS Comput Biol 8(1):e1002344
Murray SC, et al.  (2012) A pre-initiation complex at the 3'-end of genes drives antisense transcription independent of divergent sense transcription. Nucleic Acids Res 40(6):2432-44
Bircham PW, et al.  (2011) Secretory pathway genes assessed by high-throughput microscopy and synthetic genetic array analysis. Mol Biosyst 7(9):2589-98
Joshi A, et al.  (2011) Structural and functional organization of RNA regulons in the post-transcriptional regulatory network of yeast. Nucleic Acids Res 39(21):9108-17
Phenix H, et al.  (2011) Quantitative epistasis analysis and pathway inference from genetic interaction data. PLoS Comput Biol 7(5):e1002048
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
Morris RT, et al.  (2010) Ceres: software for the integrated analysis of transcription factor binding sites and nucleosome positions in Saccharomyces cerevisiae. Bioinformatics 26(2):168-74
Sharma A and Malakar P  (2010) Structure modeling and comparative genomics for epimerase enzyme (Gal10p). Bioinformation 5(6):266-70
Song C, et al.  (2010) Estimating the Stochastic Bifurcation Structure of Cellular Networks. PLoS Comput Biol 6(3):e1000699
Cantone I, et al.  (2009) A yeast synthetic network for in vivo assessment of reverse-engineering and modeling approaches. Cell 137(1):172-81
Snitkin ES, et al.  (2008) Model-driven analysis of experimentally determined growth phenotypes for 465 yeast gene deletion mutants under 16 different conditions. Genome Biol 9(9):R140
Volfson D, et al.  (2006) Origins of extrinsic variability in eukaryotic gene expression. Nature 439(7078):861-4
Zhu J, et al.  (2006) A Bayesian Network Driven Approach to Model the Transcriptional Response to Nitric Oxide in Saccharomyces cerevisiae. PLoS ONE 1:e94
Racunas SA, et al.  (2004) HyBrow: a prototype system for computer-aided hypothesis evaluation. Bioinformatics 20 Suppl 1:I257-I264
de Atauri P, et al.  (2004) Evolution of 'design' principles in biochemical networks. Syst Biol (Stevenage) 1(1):28-40
Gao J, et al.  (2003) Changes in the protein expression of yeast as a function of carbon source. J Proteome Res 2(6):643-9
Gat-Viks I and Shamir R  (2003) Chain functions and scoring functions in genetic networks. Bioinformatics 19 Suppl 1:i108-17
Kellis M, et al.  (2003) Sequencing and comparison of yeast species to identify genes and regulatory elements. Nature 423(6937):241-54
Ideker T, et al.  (2000) Testing for differentially-expressed genes by maximum-likelihood analysis of microarray data. J Comput Biol 7(6):805-17