Computational Biology of Transcription Factor Binding by Istvan Ladunga (auth.), Istvan Ladunga (eds.)

By Istvan Ladunga (auth.), Istvan Ladunga (eds.)

Through nice experimental trouble, we’ve witnessed fast, the most important advancements on the intersection of computational biology, experimental expertise, and data by which the important technique of transcriptional law should be extra tested. In Computational Biology of Transcription issue Binding, specialists within the box study the fundamental ideas and supply specific counsel for the computational analyses and organic interpretations of transcription issue binding, whereas disclosing serious useful info and caveats which are lacking from many study courses. the quantity serves not just computational biologists yet experimentalists in addition, who will want to larger know how to layout and execute experiments and to speak extra successfully with computational biologists, computing device scientists, and statisticians. Written for the hugely winning tools in Molecular Biology™ sequence, this paintings offers the type of unique description and implementation suggestion that's an important for buying optimum ends up in the lab. Authoritative and straightforward to exploit, Computational Biology of Transcription issue Binding publications scientists operating during this quarter and calls for not just new experiments but additionally the re-annotation of latest experimental facts and computational predictions resulting in very important ongoing, significant paradigm adjustments for us all.

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It is now clear that promoters with TATA boxes are not the rule but the exception, and that several other less-known promoter elements are important, too. Added to that the combinatorial complexity of enhancer and silencer interaction, together with recent discoveries with regard to 3D localization and epigenetic control, has made clear that the ‘textbook’ models of gene regulation are now severely outdated. Acknowledgements The author is partly supported through the National Science Foundation grant EPSCoR EPS-0701892.

Genes Dev 19, 2418–2423. 20. G. (2007) TFIIB and the regulation of transcription by RNA polymerase II. Chromosoma 116, 417–429. 21. P. (2006) The features of Drosophila core promoters revealed by statistical analysis. BMC Genomics 7, 161. 22. T. (2000) The downstream promoter element DPE appears to be as widely used as the TATA box in Drosophila core promoters. Mol Cell Biol 20, 4754–4764. 41 23. T. (1996) Drosophila TFIID binds to a conserved downstream basal promoter element that is present in many TATA-box-deficient promoters.

B. et al. (2006) An improved map of conserved regulatory sites for Saccharomyces cerevisiae. BMC Bioinformatics 7, 113. , and Tompa, M. (2004) PhyME: a probabilistic algorithm for finding motifs in sets of orthologous sequences. BMC Bioinformatics 5, 170. , and van Nimwegen, E. (2005) PhyloGibbs: a Gibbs sampling motif finder that incorporates phylogeny. PLoS Comput Biol 1, e67. H. (2001) Genomic regulatory systems: development and evolution. Academic Press, New York, NY. , Chen, X. et al. (2006) Genome-wide computational prediction of transcriptional regulatory modules reveals new insights into human gene expression.

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