Bayesian Analysis of Gene Expression Data
Regular price
€87.99
14 days return policy
Shipping & Delivery
A01=Bani K. Mallick
A01=David Gold
A01=Veera Baladandayuthapani
advent
analysis
Author_Bani K. Mallick
Author_David Gold
Author_Veera Baladandayuthapani
bayesian
bioinformatics
book
Category=PBT
Category=PSAK
Category=PSAX
central
data
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
exclusively
experimentation
expression
field
future
gene
genetic
highthroughput
integration
knowledge
methods
mining
new
rapidly
role
venues
Product details
- ISBN 9780470517666
- Weight: 499g
- Dimensions: 160 x 236mm
- Publication Date: 24 Jul 2009
- Publisher: John Wiley & Sons Inc
- Publication City/Country: US
- Product Form: Hardback
Secure
checkout
Fast Shipping
Easy returns
The field of high-throughput genetic experimentation is evolving rapidly, with the advent of new technologies and new venues for data mining. Bayesian methods play a role central to the future of data and knowledge integration in the field of Bioinformatics. This book is devoted exclusively to Bayesian methods of analysis for applications to high-throughput gene expression data, exploring the relevant methods that are changing Bioinformatics. Case studies, illustrating Bayesian analyses of public gene expression data, provide the backdrop for students to develop analytical skills, while the more experienced readers will find the review of advanced methods challenging and attainable.
This book:
- Introduces the fundamentals in Bayesian methods of analysis for applications to high-throughput gene expression data.
- Provides an extensive review of Bayesian analysis and advanced topics for Bioinformatics, including examples that extensively detail the necessary applications.
- Accompanied by website featuring datasets, exercises and solutions.
Bayesian Analysis of Gene Expression Data offers a unique introduction to both Bayesian analysis and gene expression, aimed at graduate students in Statistics, Biomedical Engineers, Computer Scientists, Biostatisticians, Statistical Geneticists, Computational Biologists, applied Mathematicians and Medical consultants working in genomics. Bioinformatics researchers from many fields will find much value in this book.
Bani Mallick, Department of Statistics, Texas A&M University, USA.
Veera Balandandayuthapani, Department of Biostatistics, Anderson Cancer Center, Texas, USA.
David L. Gold, Department of Biostatistics, School of Public Health and Health Professions, University at Buffalo, The State University of New York, USA.
