o f t i t l e s , v i s i t u s a t w w w. c r c p r e s s . c o m Statistical and Computational Pharmacogenomics
Python for Bioinformatics
Rongling Wu
University of Florida, Gainesville, USA
Universidad Nacional de Quilmes, Bernal, Argentina Series: Chapman & Hall/CRC Mathematical & Computational Biology
Min Lin
Duke Clinical Research Institute, Durham, North Carolina, USA Series: Interdisciplinary Statistics
Python is a popular computer language used in a wide range of applications, from peer-to-peer software to dynamic generated web pages. Python for Bioinformatics provides an accessible introduction to both the Python and BioPython languages. The book addresses advanced topics, from web applications and XML to databases and version control. In addition to useful appendices with reference material on biological file formats, the book presents commented working code and new programming techniques, such as error handling, functions, and modules. It also includes source code as well as a companion CD-ROM that contains a virtual machine with complete installation and a working web server.
Due to the tremendous accumulation of data for genetic markers, pharmacogenomics, the study of the functions and interactions of all genes in the overall variability of drug response, is one of the hottest areas of research in biomedical science. Statistical and Computational Pharmacogenomics presents recent developments in statistical methodology with a number of detailed worked examples that outline how these methods can be applied. This comprehensive volume provides key tools needed to understand and model the genetic variation for drug response and equips statisticians with a thorough understanding of this complex field and how computational skills can be employed.
Catalog no. C9292, ISBN: 978-1-58488-929-8 May 2009, 6-1/8 x 9-1/4, 456 pp., Soft Cover Suggested Price: $59.95 / £36.99
Catalog no. C8288, ISBN: 978-1-58488-828-4 January 2009, 6-1/8 x 9-1/4, 368 pp. Suggested Price: $79.95 / £44.99
Bioinformatics
Sebastian Bassi
Textbook
R Programming for Bioinformatics Robert Gentleman
Statistics in Human Genetics and Molecular Biology
121
Fred Hutchinson Cancer Research Center, Washington, USA
Cavan Reilly
Series: Chapman & Hall/CRC Computer Science & Data Analysis
Chapman & Hall/CRC Texts in Statistical Science Series
Drawing on the author’s first-hand experiences as an expert in R, this practical guide focuses on the programming skills needed to use R for the solution of bioinformatics and computational biology problems. It covers the fundamentals of the R language, objectoriented programming in R, and data mark-up and web services languages and tools. The author also examines different aspects of string handling and manipulations; discusses the interfacing of R with other languages, such as C, FORTRAN, Perl, and Python; and explains how to write software packages as well as debug and profile R code. The complete source code is available on the book’s website.
Focusing on problems in contemporary genetics and molecular biology, this text describes basic statistical methods used in genetics. It covers cluster analysis, combinatorial optimization, and dynamic programming, along with the core topics of genome mapping, biological sequence analysis, and the analysis of gene expression arrays. The author also explores Bayesian approaches, such as hidden Markov models and block motif methods, as well as modern tools of Bayesian analysis, including Markov chain Monte Carlo (MCMC). The text features a number of worked examples and problem sets at the end of each chapter.
Catalog no. C6367, ISBN: 978-1-4200-6367-7 January 2009, 6-1/8 x 9-1/4, 328 pp. Suggested Price: $69.95 / £38.99
University of Minnesota, Minneapolis, USA
Catalog no. C7263, ISBN: 978-1-4200-7263-1 June 2009, 6-1/8 x 9-1/4, 320 pp. Suggested Price: $59.95 / £36.99
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