Computational and Statistical Approaches to Genomics

  • Wei Zhang
  • Ilya Shmulevich

Table of contents

  1. Front Matter
    Pages i-ix
  2. Yidong Chen, Edward R. Dougherty, Michael L. Bittner, Paul Meltzer, Jeffery Trent
    Pages 1-19
  3. Jing Wang, Kevin R. Coombes, Keith Baggerly, Limei Hu, Stanley R. Hamilton, Wei Zhang
    Pages 21-36
  4. Kathleen F. Kerr, Edward H. Leiter, Laurent Picard, Gary A. Churchill
    Pages 37-47
  5. Keith A. Baggerly, Kevin R. Coombes, Kenneth R. Hess, David N. Stivers, Lynne V. Abruzzo, Wei Zhang
    Pages 49-59
  6. Merja Oja, Janne Nikkilä, Petri Törönen, Garry Wong, Eero Castrén, Samuel Kaski
    Pages 61-74
  7. Ciprian D. Giurcaneanu, Cristian Mircean, Gregory N. Fuller, Ioan Tabus
    Pages 89-118
  8. Edward R. Dougherty, Sanju N. Attoor
    Pages 119-136
  9. Karen M. Bloch, Gonzalo R. Arce
    Pages 137-161
  10. Ricardo Z. N. Vêncio, Helena Brentani
    Pages 209-233
  11. Harri Lähdesmäki, Ilya Shmulevich, Olli Yli-Harja, Jaakko Astola
    Pages 259-278
  12. Eugene van Someren, Lodewyk Wessels, Marcel Reinders, Eric Backer
    Pages 279-295
  13. Edward B. Suh, Edward R. Dougherty, Seungchan Kim, Michael L. Bittner, Yidong Chen, Daniel E. Russ et al.
    Pages 297-310
  14. Rudy Guerra, Zhaoxia Yu
    Pages 311-349
  15. Back Matter
    Pages 405-416

About this book


Computational and Statistical Approaches to Genomics, 2nd Edition, aims to help researchers deal with current genomic challenges. During the three years after the publication of the first edition of this book, the computational and statistical research in genomics have become increasingly more important and indispensable for understanding cellular behavior under a variety of environmental conditions and for tackling challenging clinical problems. In the first edition, the organizational structure was: data à analysis à synthesis à application. In the second edition, the same structure remains, but the chapters that primarily focused on applications have been deleted.

This decision was motivated by several factors. Firstly, the main focus of this book is computational and statistical approaches in genomics research. Thus, the main emphasis is on methods rather than on applications. Secondly, many of the chapters already include numerous examples of applications of the discussed methods to current problems in biology.

The range of topics have been broadened to include newly contributed chapters on topics such as alternative splicing, tissue microarray image and data analysis, single nucleotide polymorphisms, serial analysis of gene expression, and gene shaving. Additionally, a number of chapters have been updated or revised.

This book is for any researcher, in academia and industry, in biology, computer science, statistics, or engineering involved in genomic problems. It can also be used as an advanced level textbook in a course focusing on genomic signals, information processing, or genome biology.


Microarray Single Nucleotide Polymorphism Termination classification complexity data analysis gene expression genes hybridization image analysis modeling proving statistics visualization

Editors and affiliations

  • Wei Zhang
    • 1
  • Ilya Shmulevich
    • 2
  1. 1.M.D. Anderson Cancer CenterUniversity of TexasUSA
  2. 2.Institute for Systems BiologySeattle

Bibliographic information

Industry Sectors
Chemical Manufacturing
Consumer Packaged Goods