Computational Biology of Transcription Factor Binding

ISBN-13: 9781607618539 / Angielski / Twarda / 2010 / 454 str.

Istvan Ladunga

Opis

Transcriptional regulation controls the basic processes of life. Its complex, dynamic, and hierarchical networks control the momentary availability of messenger RNAs for protein synthesis. Transcriptional regulation is key to cell division, development, tissue differen- ation, and cancer as discussed in Chapters 1 and 2. We have witnessed rapid, major developments at the intersection of computational biology, experimental technology, and statistics. A decade ago, researches were struggling with notoriously challenging predictions of isolated binding sites from low-throughput experiments. Now we can accurately predict cis-regulatory modules, conserved cl- ters of binding sites (Chapters 13 and 15), partly based on high-throughput ch- matin immunoprecipitation experiments in which tens of millions of DNA segments are sequenced by massively parallel, next-generation sequencers (ChIP-seq, Chapters 9, 10, and 11). These spectacular developments have allowed for the genome-wide mappings of tens of thousands of transcription factor binding sites in yeast, bacteria, mammals, insects, worms, and plants. Please also note the no less spectacular failures in many laboratories around the world.

Recenzje

From the reviews:

"Gives us an overview of transcription and its regulation. ... The methods are very up-to-date and clearly presented by authors ... . The use of tools for predicting transcription factors binding sites is also very carefully presented in a text that is accessible for beginners ... . In summary, this book presents an important tool for entering the growing field of bioinformatics and its use for the study of transcription. ... If we cannot read all books ever written, this one is a good choice." (Carla Columbano Oliveira, Brazilian Journal of Pharmaceutical Sciences, Vol. 47 (2), Summer, 2011)

Spis treści

1. An Overview of the Computational Analyses and Discovery of Transcription Factor Binding Sites Istvan Ladunga 2. Components and Mechanisms of Regulation of Gene Expression Alper Yilmaz and Erich Grotewold 3. Regulatory Regions in DNA: Promoters, Enhancers, Silencers, and Insulators Jean-Jack M. Riethoven 4. Three-Dimensional Structures of DNA-Bound Transcriptional Regulators Tripti Shrivastava and Tahir H. Tahirov 5. Identification of Promoter Regions and Regulatory Sites Victor V. Solovyev, Ilham A. Shahmuradov, and Asaf A. Salamov 6. Motif Discovery Using Expectation Maximization and Gibbs’ Sampling Gary D. Stormo 7. Probabilistic Approaches to Transcription Factor Binding Site Prediction Stefan Posch, Jan Grau, André Gohr, Jens Keilwagen, and Ivo Grosse 8. The Motif Tool Assessment Platform (MTAP) for Sequence-Based Transcription Factor Binding Site Prediction Tools Daniel Quest and Hesham Ali 9. Computational Analysis of ChIP-seq Data Hongkai Ji 10. Probabilistic Peak Calling and Controlling False Discovery Rate Estimations in Transcription Factor Binding Site Mapping from ChIP-seq Shuo Jiao, Cheryl P. Bailey, Shunpu Zhang, and Istvan Ladunga 11. Sequence Analysis of Chromatin Immunoprecipitation Data for Transcription Factors Kenzie D. MacIsaac and Ernest Fraenkel 12. Inferring Protein-DNA Interaction Parameters from SELEX Experiments Marko Djordjevic 13. Kernel-Based Identification of Regulatory Modules Sebastian J. Schultheiss 14. Identification of Transcription Factor Binding Sites Derived from Transposable Element Sequences Using ChIP-seq Andrew B. Conley and I. King Jordan 15. Target Gene Identification via Nuclear Receptor Binding Site Prediction Gabor Varga 16. Computing Chromosome Conformation James Fraser, Mathieu Rousseau, Mathieu Blanchette, and Josée Dostie 17. Large-Scale Identification and Analysis of C-Proteins Valery Sorokin, Konstantin Severinov, and Mikhail S. Gelfand 18. Evolution of cis-RegulatorySequences in Drosophila Xin He and Saurabh Sinha 19. Regulating the Regulators: Modulators of Transcription Factor Activity Logan Everett, Matthew Hansen, and Sridhar Hannenhalli 20. Annotating the Regulatory Genome Stephen B. Montgomery, Katayoon Kasaian, Steven J.M. Jones, and Obi L. Griffith 21. Computational Identification of Plant Transcription Factors and the Construction of the PlantTFDB Database Kun He, An-Yuan Guo, Ge Gao, Qi-Hui Zhu, Xiao-Chuan Liu, He Zhang, Xin Chen, Xiaocheng Gu, and Jingchu Luo 22. Practical Computational Methods for Regulatory Genomics: A cisGRN-Lexicon and cisGRN-Browser for Gene Regulatory Networks Sorin Istrail, Ryan Tarpine, Kyle Schutter, and Derek Aguiar 23. Reconstructing Transcriptional Regulatory Networks Using Three-Way Mutual Information and Bayesian Networks Weijun Luo and Peter J. Woolf 24. Computational Methods for Analyzing Dynamic Regulatory Networks Anthony Gitter, Yong Lu, and Ziv Bar-Joseph

Blurb

Through great experimental difficulty, we’ve witnessed rapid, crucial developments at the intersection of computational biology, experimental technology, and statistics through which the vital process of transcriptional regulation can be further examined. In Computational Biology of Transcription Factor Binding, experts in the field examine the basic principles and provide detailed guidance for the computational analyses and biological interpretations of transcription factor binding, while disclosing critical practical information and caveats that are missing from many research publications. The volume serves not only computational biologists but experimentalists as well, who may want to better understand how to design and execute experiments and to communicate more effectively with computational biologists, computer scientists, and statisticians. Written for the highly successful Methods in Molecular Biology™ series, this work provides the kind of detailed description and implementation advice that is crucial for getting optimal results in the lab. Authoritative and easy to use, Computational Biology of Transcription Factor Binding guides scientists working in this area and demands not only new experiments but also the re-annotation of existing experimental data and computational predictions leading to important ongoing, major paradigm changes for us all.