Bioinformatics: Problem Solving Paradigms

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There are fundamental principles for problem analysis and algorithm design that are continuously used in bioinformatics. This book concentrates on a clear presentation of these principles, presenting them in a self-contained, mathematically clear and precise manner, and illustrating them with lots of case studies from main fields of bioinformatics (e.g. sequencing and mapping, string storage and manipulation, pattern matching, alignment, gene identification, genome rearrangement, structure prediction, regulatory networks, pseudoknot detection). Emphasis is laid on algorithmic "pearls" of bioinformatics, showing that things may get rather simple when taking a proper view into them. The book closes with a thorough bibliography, ranging from classic research results to very recent findings, providing many pointers for future research. Overall, this volume is ideally suited for a senior undergraduate or graduate course on bioinformatics, with a strong focus on its mathematical and computer science background.

This book highlights basic paradigms of problem analysis and algorithm design in the context of core bioinformatics problems. Mathematically demanding themes are put across to the reader by properly chosen representations with the aid of lots of illustrations.

(Prof. Dr. Amitava Datta, UWA, Perth, Australia)

Written by a theoretical computer scientist, the book perfectly complements standard textbooks from the point of view of problem solving methods continuously applied in bioinformatics.

(Prof. Dr. Georg Fuellen, Univ. Greifswald, Germany)

Author(s): Volker Sperschneider (auth.)
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2008

Language: English
Commentary: 87038
Pages: 290
Tags: Computational Biology/Bioinformatics; Algorithm Analysis and Problem Complexity

Front Matter....Pages I-XVIII
Core Bioinformatics Problems....Pages 1-24
Turning to Algorithmic Problems....Pages 25-60
Dynamic Programming....Pages 61-95
Intelligent Data Structures....Pages 97-166
NP-Hardness of Core Bioinformatics Problems....Pages 167-216
Approximation Algorithms....Pages 217-248
A Selection of Metaheuristics and Various Projects....Pages 249-277
Back Matter....Pages 279-289