Introduction to Computational Biology: An Evolutionary Approach
Analysis of molecular sequence data is the main subject of this introduction to computational biology. There are two closely connected aspects to biological sequences: (i) their relative position in the space of all other sequences, and (ii) their movement through this sequence space in evolutionary time. Accordingly, the first part of the book deals with classical methods of sequence analysis: pairwise alignment, exact string matching, multiple alignment, and hidden Markov models. In the second part evolutionary time takes center stage and phylogenetic reconstruction, the analysis of sequence variation, and the dynamics of genes in populations are explained in detail. In addition, the book contains a computer program with a graphical user interface that allows the reader to experiment with a number of key concepts developed by the authors.

This textbook is intended for students enrolled in courses in computational biology or bioinformatics as well as for molecular biologists, mathematicians, and computer scientists.

1111394115
Introduction to Computational Biology: An Evolutionary Approach
Analysis of molecular sequence data is the main subject of this introduction to computational biology. There are two closely connected aspects to biological sequences: (i) their relative position in the space of all other sequences, and (ii) their movement through this sequence space in evolutionary time. Accordingly, the first part of the book deals with classical methods of sequence analysis: pairwise alignment, exact string matching, multiple alignment, and hidden Markov models. In the second part evolutionary time takes center stage and phylogenetic reconstruction, the analysis of sequence variation, and the dynamics of genes in populations are explained in detail. In addition, the book contains a computer program with a graphical user interface that allows the reader to experiment with a number of key concepts developed by the authors.

This textbook is intended for students enrolled in courses in computational biology or bioinformatics as well as for molecular biologists, mathematicians, and computer scientists.

54.99 In Stock
Introduction to Computational Biology: An Evolutionary Approach

Introduction to Computational Biology: An Evolutionary Approach

by Bernhard Haubold, Thomas Wiehe
Introduction to Computational Biology: An Evolutionary Approach

Introduction to Computational Biology: An Evolutionary Approach

by Bernhard Haubold, Thomas Wiehe

(2006)

$54.99 
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Overview

Analysis of molecular sequence data is the main subject of this introduction to computational biology. There are two closely connected aspects to biological sequences: (i) their relative position in the space of all other sequences, and (ii) their movement through this sequence space in evolutionary time. Accordingly, the first part of the book deals with classical methods of sequence analysis: pairwise alignment, exact string matching, multiple alignment, and hidden Markov models. In the second part evolutionary time takes center stage and phylogenetic reconstruction, the analysis of sequence variation, and the dynamics of genes in populations are explained in detail. In addition, the book contains a computer program with a graphical user interface that allows the reader to experiment with a number of key concepts developed by the authors.

This textbook is intended for students enrolled in courses in computational biology or bioinformatics as well as for molecular biologists, mathematicians, and computer scientists.


Product Details

ISBN-13: 9783764367008
Publisher: Birkh�user Basel
Publication date: 06/30/2006
Edition description: 2006
Pages: 328
Product dimensions: 6.69(w) x 9.61(h) x 0.36(d)

Table of Contents

Sequences in Space.- Optimal Pairwise Alignment.- Biological Sequences and the Exact String Matching Problem.- Fast Alignment: Genome Comparison and Database Searching.- Multiple Sequence Alignment.- Sequence Profiles and Hidden Markov Models.- Gene Prediction.- Sequences in Time.- Phylogeny.- Sequence Variation and Molecular Evolution.- Genes in Populations: Forward in Time.- Genes in Populations: Backward in Time.- Testing Evolutionary Hypotheses.
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