Algorithms in Bioinformatics

A Practical Introduction

AvWing-Kin Sung

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PDF, Engelska, 2009

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Beskrivning

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 bi

Produktinformation

Utgivningsdatum:2009-11-24
Språk:Engelska
Filformat:PDF
Kopieringsskydd:LCP
ISBN:9781420070347
Förlag:Taylor & Francis Ltd
Serie:Chapman & Hall/CRC Computational Biology Series

Utforska kategorier

Biovetenskap inom Naturvetenskap och teknik
Programmeringsböcker inom Data och IT

Mer om författaren

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

Recensioner i media

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

Innehållsförteckning

Introduction to Molecular Biology. Sequence Similarity. Suffix Tree. Database Search. Multiple Sequence Alignment. Genome Alignment. Phylogeny Reconstruction. Phylogeny Comparison. Genome Rearrangement. Motif Finding. RNA Secondary Structure Prediction. Peptide Sequencing. Population Genetics. References. Index.