Computational Biology of Transcription Factor Binding (Methods in Molecular Biology (674))

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.

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.