Algorithms in Bioinformatics - Sung, Wing-Kin

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Auteur(s) : Sung, Wing-Kin

Editeur : Chapman And Hall/Crc

Langue : Anglais

Parution : 01/11/2009

Format : Moyen, de 350g à 1kg

Nombre de pages : 408

Expédition : 703

Dimensions : 23.6 x 15.7 x 2.6

ISBN : 1420070339

Résumé :

This classroom-tested text provides an in-depth introduction to the algorithmic techniques applied in bioinformatics. For each topic, the author clearly details the biological motivation, precisely defines the corresponding computational problems, and includes detailed examples to illustrate each algorithm. The text covers basic molecular biology concepts, sequence similarity, the suffix tree, sequence databases, sequence and genome alignment, the phylogenetic tree, genome rearrangement, motif finding, the secondary structure of RNA, peptide sequencing, and population genetics. Supplementary material is provided on the author?s website and a solutions manual is available for qualifying instructors.

Biographie:

Wing-Kin Sung is an associate professor at the National University of Singapore.

Sommaire:
Introduction to Molecular Biology DNA, RNA, Protein Genome, Chromosome, and Gene Replication and Mutation of DNA Central Dogma (From DNA to Protein) Post-Translation Modification (PTM) Population Genetics Basic Biotechnological Tools Brief History of Bioinformatics Sequence Similarity Introduction Global Alignment Problem Local Alignment Semi-Global Alignment Gap Penalty Scoring Function Suffix Tree Introduction Suffix Tree Simple Applications of Suffix Tree Construction of Suffix Tree Suffix Array FM-Index Approximate Searching Problem Database Search Introduction Smith-Waterman Algorithm FastA BLAST Variations of the BLAST Algorithm Q-Gram Alignment Based on Suffix ARrays (QUASAR) Locality-Sensitive Hashing BWT-SW Are Existing Database Searching Methods Sensitive Enough? Multiple Sequence Alignment Introduction Formal Definition of Multiple Sequence Alignment Problem Dynamic Programming Method Center Star Method Progressive Alignment Method Iterative Method Genome Alignment Introduction Maximum Unique Match (MUM) Mutation Sensitive Alignment Dot Plot for Visualizing the Alignment Phylogeny Reconstruction Introduction Character-Based Phylogeny Reconstruction Algorithm Distance-Based Phylogeny Reconstruction Algorithm Bootstrapping Can Tree Reconstruction Methods Infer the Correct Tree? Phylogeny Comparison Introduction Similarity Measurement Dissimilarity Measurements Consensus Tree Problem Genome Rearrangement Introduction Types of Genome Rearrangements Computational Problems Sorting Unsigned Permutation by Reversals Sorting Signed Permutation by Reversals Motif Finding Introduction Identifying Binding Regions of TFs Motif Model The Motif Finding Problem Scanning for Known Motifs Statistical Approaches Combinatorial Approaches Scoring Function Motif Ensemble Methods Can Motif Finders Discover the Correct Motifs? Motif Finding Utilizing Additional Information RNA Secondary Structure Prediction Introduction Obtaining RNA Secondary Structure Experimentally RNA Structure Prediction Based on Sequence Only Structure Prediction with the Assumption That There Is No Pseudoknot Nussinov Folding Algorithm ZUKER Algorithm Structure Prediction with Pseudoknots Peptide Sequencing Introduction Obtaining the Mass Spectrum of a Peptide Modeling the Mass Spectrum of a Fragmented Peptide De novo Peptide Sequencing Using Dynamic Programming De novo Sequencing Using Graph-Based Approach Peptide Sequencing via Database Search Population Genetics Introduction Hardy-Weinberg Equilibrium Linkage Disequilibrium Genotype Phasing Tag SNP Selection Association Study References Index Exercises appear at the end of each chapter.

This aptly titled book is a timely publication that details several algorithms widely used in bioinformatics. ! This work can serve as a reference guide for students and researchers attempting to implement or learn algorithms relevant to bioinformatics. Although some concepts referenced in the book specifically target advanced bioinformatics experts, general users should not be discouraged from reading this work. !Summing Up: Recommended. --CHOICE, June 2010 ! an excellent guide. The book is appropriate for advanced undergraduates and graduates in mathematics or CS. ! The 27-page introduction is the most efficient concept-building summary and explication of molecular biology that I have encountered. ! Section 1.8 sets a new, high standard for science-history exposition, covering Gregor Mendel to the present. !This self-contained, well-designed, and well-written book, with its many good exercises, bibliographic references, and photo-quality figures, is an ideal introduction to bioinformatics. --George Hacken, Computing Reviews, March 2010