Statistical Modeling and Machine Learning for Molecular Biology (Chapman & Hall/CRC Mathematical and Computational Biology)

Alan Moses

ISBN 10: 1482258595 / ISBN 13: 9781482258592

Published by Chapman and Hall/CRC, 2017

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Bibliographic Details

• Title: Statistical Modeling and Machine Learning for Molecular Biology (Chapman & Hall/CRC Mathematical and Computational Biology)
• Publisher: Chapman and Hall/CRC
• Publication Date: 2017
• Language: English
• ISBN 10: 1482258595
• ISBN 13: 9781482258592
• Binding: Softcover
• Condition: New
• Seller catalogs:
  • COMPUTER SCIENCE

About this title

Synopsis

Molecular biologists are performing increasingly large and complicated experiments, but often have little background in data analysis. The book is devoted to teaching the statistical and computational techniques molecular biologists need to analyze their data. It explains the big-picture concepts in data analysis using a wide variety of real-world molecular biological examples such as eQTLs, ortholog identification, motif finding, inference of population structure, protein fold prediction and many more. The book takes a pragmatic approach, focusing on techniques that are based on elegant mathematics yet are the simplest to explain to scientists with little background in computers and statistics.

About the Author

Alan M Moses is currently Associate Professor and Canada Research Chair in Computational Biology in the Departments of Cell & Systems Biology and Computer Science at the University of Toronto. His research touches on many of the major areas in computational biology, including DNA and protein sequence analysis, phylogenetic models, population genetics, expression profiles, regulatory network simulations and image analysis.