Time Warps, String Edits and Macromolecules: Theory and Practice of Sequence Comparison

Sankoff, David

ISBN 10: 0201078090 / ISBN 13: 9780201078091

Published by addison Wesley, 1983

About this Item

First edition Book in very good condition Neat signature on front endpaper. Contents in fine condition Wear to top and base spine and on tips corners. Seller Inventory # ABE-1518550242293

Bibliographic Details

Title: Time Warps, String Edits and Macromolecules:...

Publisher: addison Wesley

Publication Date: 1983

Binding: Hardcover

Condition: Very Good

Edition: 1st Edition

About this title

Synopsis:

Time Warps, String Edits and Macromolecules is a young classic in computational science. The computational perspective is that of sequence processing, in particular the problem of recognizing related sequences. The book is the first, and still best compilation of papers explaining how to measure distance between sequences, and how to compute that measure effectively. This is called string distance, Levenshtein distance, or edit distance. The book contains lucid explanations of the basic techniques; well-annotated examples of applications; mathematical analysis of its computational (algorithmic) complexity; and extensive discussion of the variants needed for weighted measures, timed sequences (songs), applications to continuous data, comparison of multiple sequences and extensions to tree-structures. This theory finds applications in molecular biology, speech recognition, analysis of bird song and error correcting in computer software.

Book Description:

Time Warps, String Edits and Macromolecules is a young classic in computational science, scientific analysis from a computational perspective. The book is the first, and still best compilation of papers explaining how to measure distance between sequences, and how to compute that measure effectively. The book contains lucid explanations of the basic techniques, well-annotated examples of applications, and mathematical analysis of its computational (algorithmic) complexity.