Combinatorial Pattern Matching Algorithms in Computational Biology Using Perl and R

Gross, Louis J. (Series edited by)/ Lenhart, Suzanne (Series edited by)/ Maini, Philip K. (Series edited by)/ Etheridge, Alison M. (Series edited by)/ Voit, Eberhard O. (Series edited by)/ Ranganathan, Shoba (Series edited by)/ Safer, Hershel (Series edited by)/ Valiente, Gabriel (Author)

ISBN 10: 142006973X / ISBN 13: 9781420069730

Edité par Chapman & Hall, 2009

A propos de cet article

1st edition. 368 pages. 9.53x6.38x0.98 inches. In Stock. N° de réf. du vendeur __142006973X

Détails bibliographiques

Titre : Combinatorial Pattern Matching Algorithms in...

Éditeur : Chapman & Hall

Date d'édition : 2009

Reliure : Hardcover

Etat : Brand New

A propos de ce titre

Synopsis :

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.

À propos de l?auteur:

Gabriel Valiente is Associate Professor in the Department of Software at the Technical University of Catalonia. His research interests include computational biology, bioinformatics, exact and approximate matching in graphs and patterns, and graph transformation.