Algorithms on strings, trees, and sequences : computer science and computational biology

By:

Gusfield, Dan

Material type: Text

TextPublication details: New York Cambridge 1997Description: 534pISBN:

9780521670357

Subject(s):

DDC classification:

005.73 GUS

Summary: Traditionally an area of study in computer science, string algorithms have, in recent years, become an increasingly important part of biology, particularly genetics. This volume is a comprehensive look at computer algorithms for string processing. In addition to pure computer science, Gusfield adds extensive discussions on biological problems that are cast as string problems and on methods developed to solve them. This text emphasizes the fundamental ideas and techniques central to today's applications. New approaches to this complex material simplify methods that up to now have been for the specialist alone. With over 400 exercises to reinforce the material and develop additional topics, the book is suitable as a text for graduate or advanced undergraduate students in computer science, computational biology, or bio-informatics.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Book	Plaksha University Library	Computer science	005.73 GUS (Browse shelf(Opens below))	Available		000952

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Traditionally an area of study in computer science, string algorithms have, in recent years, become an increasingly important part of biology, particularly genetics. This volume is a comprehensive look at computer algorithms for string processing. In addition to pure computer science, Gusfield adds extensive discussions on biological problems that are cast as string problems and on methods developed to solve them. This text emphasizes the fundamental ideas and techniques central to today's applications. New approaches to this complex material simplify methods that up to now have been for the specialist alone. With over 400 exercises to reinforce the material and develop additional topics, the book is suitable as a text for graduate or advanced undergraduate students in computer science, computational biology, or bio-informatics.

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