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Bioinformatics Algorithms: Techniques and Applications
Contributor(s): Mandoiu, Ion (Editor), Zelikovsky, Alexander (Editor), Pan, Yi (Editor)
ISBN: 0470097736     ISBN-13: 9780470097731
Publisher: Wiley-Interscience
OUR PRICE:   $188.05  
Product Type: Hardcover - Other Formats
Published: February 2008
Qty:
Annotation: "Bioinformatics Algorithms: Techniques and Applications" targets the future collaboration of researchers in algorithms, bioinformatics, and molecular biology. It addresses critical bioinformatics research areas of protein-protein interaction, molecular modeling in drug design, and structural biology. Some of the most important topics in the field of bioinformatics are covered with selected topics that are gaining increased interest, including drug design, gene finding, and text mining in bioinformatics.
Additional Information
BISAC Categories:
- Computers | Programming - Algorithms
- Science | Life Sciences - Biochemistry
Dewey: 572.802
LCCN: 2007034307
Series: Wiley Series on Bioinformatics: Computational Techniques and Engineering
Physical Information: 1.19" H x 6.29" W x 9.42" (1.89 lbs) 528 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
Presents algorithmic techniques for solving problems in bioinformatics, including applications that shed new light on molecular biology

This book introduces algorithmic techniques in bioinformatics, emphasizing their application to solving novel problems in post-genomic molecular biology. Beginning with a thought-provoking discussion on the role of algorithms in twenty-first-century bioinformatics education, Bioinformatics Algorithms covers:

  • General algorithmic techniques, including dynamic programming, graph-theoretical methods, hidden Markov models, the fast Fourier transform, seeding, and approximation algorithms

  • Algorithms and tools for genome and sequence analysis, including formal and approximate models for gene clusters, advanced algorithms for non-overlapping local alignments and genome tilings, multiplex PCR primer set selection, and sequence/network motif finding

  • Microarray design and analysis, including algorithms for microarray physical design, missing value imputation, and meta-analysis of gene expression data

  • Algorithmic issues arising in the analysis of genetic variation across human population, including computational inference of haplotypes from genotype data and disease association search in case/control epidemiologic studies

  • Algorithmic approaches in structural and systems biology, including topological and structural classification in biochemistry, and prediction of protein-protein and domain-domain interactions

Each chapter begins with a self-contained introduction to a computational problem; continues with a brief review of the existing literature on the subject and an in-depth description of recent algorithmic and methodological developments; and concludes with a brief experimental study and a discussion of open research challenges. This clear and approachable presentation makes the book appropriate for researchers, practitioners, and graduate students alike.