Computational Biology of Transcription Factor Binding

  • Istvan Ladunga

Part of the Methods in Molecular Biology book series (MIMB, volume 674)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Alper Yilmaz, Erich Grotewold
    Pages 23-32
  3. Tripti Shrivastava, Tahir H. Tahirov
    Pages 43-55
  4. Victor V. Solovyev, Ilham A. Shahmuradov, Asaf A. Salamov
    Pages 57-83
  5. Stefan Posch, Jan Grau, André Gohr, Jens Keilwagen, Ivo Grosse
    Pages 97-119
  6. Hongkai Ji
    Pages 143-159
  7. Sebastian J. Schultheiss
    Pages 213-223
  8. James Fraser, Mathieu Rousseau, Mathieu Blanchette, Josée Dostie
    Pages 251-268
  9. Valery Sorokin, Konstantin Severinov, Mikhail S. Gelfand
    Pages 269-282
  10. Xin He, Saurabh Sinha
    Pages 283-296
  11. Logan Everett, Matthew Hansen, Sridhar Hannenhalli
    Pages 297-312
  12. Stephen B. Montgomery, Katayoon Kasaian, Steven J.M. Jones, Obi L. Griffith
    Pages 313-349
  13. Kun He, An-Yuan Guo, Ge Gao, Qi-Hui Zhu, Xiao-Chuan Liu, He Zhang et al.
    Pages 351-368
  14. Anthony Gitter, Yong Lu, Ziv Bar-Joseph
    Pages 419-441
  15. Back Matter
    Pages 443-454

About this book


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.


Annotation ChIP-seq Genome browsers Motif discovery tools Promoter Statistics Transcriptional regulation cis-Regulatory modules gene expression genes genome molecular biology sequence analysis transcription

Editors and affiliations

  • Istvan Ladunga
    • 1
  1. 1., Department of StatisticsUniversity of Nebraska-LincolnLincolnUSA

Bibliographic information

  • DOI
  • Copyright Information Springer Science+Business Media, LLC 2010
  • Publisher Name Humana Press, Totowa, NJ
  • eBook Packages Springer Protocols
  • Print ISBN 978-1-60761-853-9
  • Online ISBN 978-1-60761-854-6
  • Series Print ISSN 1064-3745
  • Series Online ISSN 1940-6029
  • Buy this book on publisher's site