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Introduction to Computational Biology : Maps, Sequences and Genomes

By: (Author) Michael S. Waterman

Manufacture on Demand

Ksh 24,300.00

Format: Hardback or Cased Book

ISBN-10: 0412993910

ISBN-13: 9780412993916

Series: Chapman & Hall/CRC Interdisciplinary Statistics

Publisher: Taylor & Francis Ltd

Imprint: Chapman & Hall/CRC

Country of Manufacture: US

Country of Publication: GB

Publication Date: Jun 1st, 1995

Print length: 448 Pages

Weight: 768 grams

Dimensions (height x width x thickness): 24.50 x 16.30 x 2.90 cms

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Biology is at the beginning of a new era, promising significant discoveries that will be characterized by information-packed databases. This text offers a textbook treatment of the combinatorial and statistical problems that will arise in this new era.
Biology is in the midst of a era yielding many significant discoveries and promising many more. Unique to this era is the exponential growth in the size of information-packed databases. Inspired by a pressing need to analyze that data, Introduction to Computational Biology explores a new area of expertise that emerged from this fertile field- the combination of biological and information sciences.

This introduction describes the mathematical structure of biological data, especially from sequences and chromosomes. After a brief survey of molecular biology, it studies restriction maps of DNA, rough landmark maps of the underlying sequences, and clones and clone maps. It examines problems associated with reading DNA sequences and comparing sequences to finding common patterns. The author then considers that statistics of pattern counts in sequences, RNA secondary structure, and the inference of evolutionary history of related sequences.

Introduction to Computational Biology exposes the reader to the fascinating structure of biological data and explains how to treat related combinatorial and statistical problems. Written to describe mathematical formulation and development, this book helps set the stage for even more, truly interdisciplinary work in biology.

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