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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.
This text investigates the fundamental mathematical and computational methodologies required to measure distance between sequences and compute those measures with optimal efficiency. David Sankoff, a prominent researcher in computational biology and linguistics, compiles a foundational set of papers that establish the framework for string distance, Levenshtein distance, and edit distance. The work provides a rigorous analysis of algorithmic complexity while demonstrating how these techniques apply to diverse fields ranging from molecular biology to speech recognition.
What You Will Find
Experts recognize this volume as a foundational text in the field of computational sequence processing. Readers frequently note the technical clarity of the explanations, which bridge the gap between abstract mathematical theory and practical implementation in software and biological research.
Page Count:
382
Publication Date:
1983-01-01
Publisher:
Addison-Wesley
ISBN-10:
0201078090
ISBN-13:
9780201078091
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