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![]( "Buchcover ISBN 9780470253427")
„This clear and approachable presentation makes the book appropriate for researchers, practioners, and graduate students.“ (Mathematical Reviews, Issue 2009b)
"This volume will be a nice addition to the bioinformatician's bookshelf." (Quarterly Review of Biology, December 2008)
Presents algorithmic techniques for solving problems inbioinformatics, including applications that shed new light onmolecular biology
This book introduces algorithmic techniques in bioinformatics, emphasizing their application to solving novel problems inpost-genomic molecular biology. Beginning with a thought-provokingdiscussion on the role of algorithms in twenty-first-centurybioinformatics education, Bioinformatics Algorithms covers:
* General algorithmic techniques, including dynamic programming, graph-theoretical methods, hidden Markov models, the fast Fouriertransform, seeding, and approximation algorithms
* Algorithms and tools for genome and sequence analysis, includingformal and approximate models for gene clusters, advancedalgorithms for non-overlapping local alignments and genome tilings, multiplex PCR primer set selection, and sequence/network motiffinding
* Microarray design and analysis, including algorithms formicroarray physical design, missing value imputation, andmeta-analysis of gene expression data
* Algorithmic issues arising in the analysis of genetic variationacross human population, including computational inference ofhaplotypes from genotype data and disease association search incase/control epidemiologic studies
* Algorithmic approaches in structural and systems biology, including topological and structural classification inbiochemistry, and prediction of protein-protein and domain-domaininteractions
Each chapter begins with a self-contained introduction to acomputational problem; continues with a brief review of theexisting literature on the subject and an in-depth description ofrecent algorithmic and methodological developments; and concludeswith a brief experimental study and a discussion of open researchchallenges. This clear and approachable presentation makes the bookappropriate for researchers, practitioners, and graduate studentsalike.
This book introduces algorithmic techniques in bioinformatics, emphasizing their application to solving novel problems inpost-genomic molecular biology. Beginning with a thought-provokingdiscussion on the role of algorithms in twenty-first-centurybioinformatics education, Bioinformatics Algorithms covers:
* General algorithmic techniques, including dynamic programming, graph-theoretical methods, hidden Markov models, the fast Fouriertransform, seeding, and approximation algorithms
* Algorithms and tools for genome and sequence analysis, includingformal and approximate models for gene clusters, advancedalgorithms for non-overlapping local alignments and genome tilings, multiplex PCR primer set selection, and sequence/network motiffinding
* Microarray design and analysis, including algorithms formicroarray physical design, missing value imputation, andmeta-analysis of gene expression data
* Algorithmic issues arising in the analysis of genetic variationacross human population, including computational inference ofhaplotypes from genotype data and disease association search incase/control epidemiologic studies
* Algorithmic approaches in structural and systems biology, including topological and structural classification inbiochemistry, and prediction of protein-protein and domain-domaininteractions
Each chapter begins with a self-contained introduction to acomputational problem; continues with a brief review of theexisting literature on the subject and an in-depth description ofrecent algorithmic and methodological developments; and concludeswith a brief experimental study and a discussion of open researchchallenges. This clear and approachable presentation makes the bookappropriate for researchers, practitioners, and graduate studentsalike.
