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

Alan Moses

ISBN 10: 1482258595 ISBN 13: 9781482258592

Editorial: Chapman and Hall/CRC, 2017

Idioma: Ingl�s

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Detalles bibliogr�ficos

T�tulo

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

Editor

Chapman and Hall/CRC

Fecha de publicaci�n

2017

Idioma

Ingl�s

ISBN 10

1482258595

ISBN 13

9781482258592

Encuadernaci�n

Softcover

Estado

New

Cat�logos de vendedores

COMPUTER SCIENCE

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Sinopsis

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.

Acerca del autor

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.

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