Hardback : £160.00
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.
Show moreEmphasizing 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.
Show moreIntroduction. SEQUENCE PATTERN MATCHING: Sequences. Simple Pattern Matching in Sequences. General Pattern Matching in Sequences. TREE PATTERN MATCHING: Trees. Simple Pattern Matching in Trees. General Pattern Matching in Trees. GRAPH PATTERN MATCHING: Graphs. Simple Pattern Matching in Graphs. General Pattern Matching in Graphs. Appendices. References. Index.
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.
I like the hands-on approach this book offers, and the very
pedagogical structure it follows … . The book also has tons of
examples, thoughtfully chosen and beautifully laid out … the book
is very well-written and accessible, undoubtedly written by an
author who takes great care in preparing his manuscripts and
teaching about an area he enjoys working on.
—Anthony Labarre, SIGACT News, July 2012This text provides a solid
foundation to the field. It will work as a practical handbook for
pattern matching applications in computational biology.
—Michael Goldberg, Computing Reviews, February 2010… the book makes
a clear distinction between problems that emerge in the analysis of
the structure and in the comparative analysis of two or more
structures. … Well-known computational biology tools that allow
searching nucleotide and protein databases for local sequence
alignment are based on CPM algorithms only. The techniques
presented in this book go beyond that. … detailed algorithm
solutions in pseudocode, full Perl and R implementation, and
pointers to software and implementation are presented. This … is
what makes Valiente’s effort unique. …
—Ernesto D’Avanzo, Computing Reviews, February 2010… It is a
well-sorted collection of pattern matching algorithms that are used
to work with problems in computational biology. … You can find all
of the sources on the author’s website, which come in handy when
you actually want to use them, since you do not have to retype
them. And there is an introduction to Perl as well as to R, showing
how to decode DNA/RNA-triplets to amino acids and giving some basic
overview over standard functions. … I certainly recommend this as
an introduction and reference to some algorithms of pattern
matching in computational biology. You actually learn how
algorithms over the most important data types are designed in a
straightforward, logical way. …
—Jannik Pewny, IACR Book Reviews, 2009…after a few minutes of
random browsing, I was left with a feeling of total appreciation of
the book, admiration for Prof. Gabriel Valiente, and a realization
that this book will be part of my fundamental library for me and my
group from the moment it is published. There are so many good
things to say that I do not know where to start. The organization
is straightforward with major sections that extend from simple
sequences to trees to graphs. … This parallel structure makes it
easy to apply lessons used on the simplest object (sequences) to
objects of medium (trees) and significant (graphs) difficulty. …a
wonderful way to learn leveraging … The Perl is beautifully clear
and the examples have already taught me how to improve my own
code.
—Michael Levitt, Professor and Chair, Department of Structural
Biology, Stanford University, California, USA…Balancing a careful
mixture of formal methods, programming, and examples, Gabriel
Valiente has managed to harmoniously bridge languages and contents
into a self-contained source of lasting influence. It is not
difficult to predict that this book will be studied indifferently
by the specialist of biology and computer science, helping each to
walk a few steps toward the other. It will entice new generations
of scholars to engage in its beautiful subject.
—From the Foreword, Alberto Apostolico, Professor, College of
Computing, Georgia Tech, Atlanta, USAUnlocks the power for R for
Perl programmers, and vice versa. Reveals R to be a powerful and
accessible tool for bioinformatics. The title is a mouthful, but
the use of both R and Perl for bioinformatics is revealing.
—Steven Skiena, Professor, Department of Computer Science, Stony
Brook University, New York, USA
I like the hands-on approach this book offers, and the very
pedagogical structure it follows … . The book also has tons of
examples, thoughtfully chosen and beautifully laid out … the book
is very well-written and accessible, undoubtedly written by an
author who takes great care in preparing his manuscripts and
teaching about an area he enjoys working on.
—Anthony Labarre, SIGACT News, July 2012This text provides a solid
foundation to the field. It will work as a practical handbook for
pattern matching applications in computational biology.
—Michael Goldberg, Computing Reviews, February 2010… the book makes
a clear distinction between problems that emerge in the analysis of
the structure and in the comparative analysis of two or more
structures. … Well-known computational biology tools that allow
searching nucleotide and protein databases for local sequence
alignment are based on CPM algorithms only. The techniques
presented in this book go beyond that. … detailed algorithm
solutions in pseudocode, full Perl and R implementation, and
pointers to software and implementation are presented. This … is
what makes Valiente’s effort unique. …
—Ernesto D’Avanzo, Computing Reviews, February 2010… It is a
well-sorted collection of pattern matching algorithms that are used
to work with problems in computational biology. … You can find all
of the sources on the author’s website, which come in handy when
you actually want to use them, since you do not have to retype
them. And there is an introduction to Perl as well as to R, showing
how to decode DNA/RNA-triplets to amino acids and giving some basic
overview over standard functions. … I certainly recommend this as
an introduction and reference to some algorithms of pattern
matching in computational biology. You actually learn how
algorithms over the most important data types are designed in a
straightforward, logical way. …
—Jannik Pewny, IACR Book Reviews, 2009…after a few minutes of
random browsing, I was left with a feeling of total appreciation of
the book, admiration for Prof. Gabriel Valiente, and a realization
that this book will be part of my fundamental library for me and my
group from the moment it is published. There are so many good
things to say that I do not know where to start. The organization
is straightforward with major sections that extend from simple
sequences to trees to graphs. … This parallel structure makes it
easy to apply lessons used on the simplest object (sequences) to
objects of medium (trees) and significant (graphs) difficulty. …a
wonderful way to learn leveraging … The Perl is beautifully clear
and the examples have already taught me how to improve my own
code.
—Michael Levitt, Professor and Chair, Department of Structural
Biology, Stanford University, California, USA…Balancing a careful
mixture of formal methods, programming, and examples, Gabriel
Valiente has managed to harmoniously bridge languages and contents
into a self-contained source of lasting influence. It is not
difficult to predict that this book will be studied indifferently
by the specialist of biology and computer science, helping each to
walk a few steps toward the other. It will entice new generations
of scholars to engage in its beautiful subject.
—From the Foreword, Alberto Apostolico, Professor, College of
Computing, Georgia Tech, Atlanta, USAUnlocks the power for R for
Perl programmers, and vice versa. Reveals R to be a powerful and
accessible tool for bioinformatics. The title is a mouthful, but
the use of both R and Perl for bioinformatics is revealing.
—Steven Skiena, Professor, Department of Computer Science, Stony
Brook University, New York, USA
|
Ask a Question About this Product More... |
|
