Editors:
- Contains the newest research results on genomic analysis and modeling using state-of-the-art methods from engineering, statistics, and genomics
- Involves the application of these tools and models to real biological and clinical problems
- Provides new initiatives and directions for industry leaders in genomics
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (18 chapters)
-
Front Matter
-
Back Matter
About this book
The 2nd edition of this book adds 8 new contributors to reflect a modern cutting edge approach to genomics. The expanded scope includes coverage of statistical issues on single nucleotide polymorphism analysis array, CGH analysis, SAGE analysis, gene shaving and related methods for microarray data analysis, and cross-hybridization issues on oligo arrays. The authors of the 17 original chapters have updated the contents of their chapters, including references, on such topics as the development of novel engineering, statistical and computational principles, as well as methods, models, and tools from these disciplines applied to genomics.
Editors and Affiliations
-
M.D. Anderson Cancer Center, University of Texas, USA
Wei Zhang
-
Institute for Systems Biology, Seattle
Ilya Shmulevich
Bibliographic Information
Book Title: Computational and Statistical Approaches to Genomics
Editors: Wei Zhang, Ilya Shmulevich
DOI: https://doi.org/10.1007/b137323
Publisher: Springer New York, NY
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: Springer-Verlag US 2006
Hardcover ISBN: 978-0-387-26287-1Published: 04 May 2006
Softcover ISBN: 978-1-4419-3882-4Published: 19 November 2010
eBook ISBN: 978-0-387-26288-8Published: 26 December 2007
Edition Number: 2
Number of Pages: X, 416
Number of Illustrations: 5 illustrations in colour
Topics: Biochemistry, general, Cancer Research, Biotechnology, Computer Science, general, Image Processing and Computer Vision, Pattern Recognition