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Bioinformatics: The Machine Learning Approach (Adaptive Computation and Machine Learning Series)

Bioinformatics: The Machine Learning Approach (Adaptive Computation and Machine Learning Series)

Bioinformatics: The Machine Learning Approach (Adaptive Computation and Machine
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Bioinformatics: The Machine Learning Approach (Adaptive Computation and Machine Learning Series) Hardback - 1998

by Baldi, P. & Brunak, S

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  • Hardback

Description

The MIT Press, 1998. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In good all round condition. Dust jacket in good condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,950grams, ISBN:9780262024426
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Details

  • Title Bioinformatics: The Machine Learning Approach (Adaptive Computation and Machine Learning Series)
  • Author Baldi, P. & Brunak, S
  • Binding Hardback
  • Edition 2nd Printing.
  • Pages 351
  • Volumes 1
  • Language ENG
  • Publisher The MIT Press, Cumberland, Rhode Island, U.S.A.
  • Publication date 1998
  • Bookseller's Inventory # 9913979
  • ISBN 9780262024426 / 026202442X
  • Weight 1.87 lbs (0.85 kg)
  • Dimensions 9.36 x 7.33 x 1.06 in (23.77 x 18.62 x 2.69 cm)
  • Category Computers - Other Applications
  • Library of Congress subjects Markov processes, Neural networks (Computer science)
  • Library of Congress Catalogue Number 97036102
  • Dewey Decimal Code 572.801

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Reader reviews for Bioinformatics: The Machine Learning Approach (Adaptive Computation and Machine Learning Series)

From the publisher

The authors of this text present the key machine learning approaches and apply them to the computational problems encountered in the analysis of biological data. The book is aimed at two types of researchers and students: firstly those biologists and biochemists who need to understand new data-driven algorithms, such as neural networks and hidden Markov models, in the context of biological sequences and their molecular structure and function; and secondly those with a primary background in physics, mathematics, statistics or computer science who need to know more about specific applications in molecular biology.
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