Algorithms in Bioinformatics (Chapman & Hall/CRC Mathematical & Computational Biology v. 29)

Algorithms in Bioinformatics (Chapman & Hall/CRC Mathematical & Computational Biology v. 29)

By: Wing-Kin Sung (author), Eberhard O. Voit (series_editor), Shoba Ranganathan (series_editor), Alison M. Etheridge (series_editor), Louis J. Gross (series_editor), Philip K. Maini (series_editor), Hershel Safer (series_editor), Suzanne Lenhart (series_editor)Hardback

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Thoroughly Describes Biological Applications, Computational Problems, and Various Algorithmic Solutions Developed from the author's own teaching material, Algorithms in Bioinformatics: A Practical Introduction provides an in-depth introduction to the algorithmic techniques applied in bioinformatics. For each topic, the author clearly details the biological motivation and precisely defines the corresponding computational problems. He also includes detailed examples to illustrate each algorithm and end-of-chapter exercises for students to familiarize themselves with the topics. Supplementary material is available at This classroom-tested textbook begins with basic molecular biology concepts. It then describes ways to measure sequence similarity, presents simple applications of the suffix tree, and discusses the problem of searching sequence databases. After introducing methods for aligning multiple biological sequences and genomes, the text explores applications of the phylogenetic tree, methods for comparing phylogenetic trees, the problem of genome rearrangement, and the problem of motif finding. It also covers methods for predicting the secondary structure of RNA and for reconstructing the peptide sequence using mass spectrometry. The final chapter examines the computational problem related to population genetics.

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About Author

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


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.

Product Details

  • publication date: 01/10/2009
  • ISBN13: 9781420070330
  • Format: Hardback
  • Number Of Pages: 407
  • ID: 9781420070330
  • weight: 703
  • ISBN10: 1420070339

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