Combinatorial Pattern Matching Algorithms in Computational Biology Using Perl and R

Gabriel Valiente

Hardback
$83.96

eBook
from $47.00

April 8, 2009 by Chapman and Hall/CRC
Reference - 368 Pages - 89 B/W Illustrations
ISBN 9781420069730 - CAT# C6973
Series: Chapman & Hall/CRC Mathematical and Computational Biology

FREE Standard Shipping!

was $104.95

$83.96

SAVE $20.99

Add to Cart
Add to Wish List

Features

  • Presents combinatorial pattern matching problems in a uniform framework
  • Provides an intuitive presentation of the algorithms, followed by a detailed exposition in pseudo-code, making it easy to comprehend the algorithmic solutions
  • Offers alternative implementations of the algorithms in Perl and R to enable the testing of algorithms and the building of projects based on the code
  • Establishes a basis for applying and extending the latest results in the field by including material from the specialized research literature
  • Includes the Perl and R source code for all the algorithms on the author’s website

Summary

Emphasizing the search for patterns within and between biological sequences, trees, and graphs, Combinatorial Pattern Matching Algorithms in Computational Biology Using Perl and R shows how combinatorial pattern matching algorithms can solve computational biology problems that arise in the analysis of genomic, transcriptomic, proteomic, metabolomic, and interactomic data. It implements the algorithms in Perl and R, two widely used scripting languages in computational biology.

The book provides a well-rounded explanation of traditional issues as well as an up-to-date account of more recent developments, such as graph similarity and search. It is organized around the specific algorithmic problems that arise when dealing with structures that are commonly found in computational biology, including biological sequences, trees, and graphs. For each of these structures, the author makes a clear distinction between problems that arise in the analysis of one structure and in the comparative analysis of two or more structures. He also presents phylogenetic trees and networks as examples of trees and graphs in computational biology.

This book supplies a comprehensive view of the whole field of combinatorial pattern matching from a computational biology perspective. Along with thorough discussions of each biological problem, it includes detailed algorithmic solutions in pseudo-code, full Perl and R implementation, and pointers to other software, such as those on CPAN and CRAN.