Statistical Modeling and Machine Learning for Molecular Biology (Paperback)

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.

General

Imprint:	Apple Academic Press Inc.
Country of origin:	Canada
Series:	Chapman & Hall/CRC Computational Biology Series
Release date:	December 2016
First published:	2017
Authors:	Alan Moses
Dimensions:	234 x 156 x 19mm (L x W x T)
Format:	Paperback - Cloth over boards
Pages:	264
ISBN-13:	978-1-4822-5859-2
Categories:	Books > Science & Mathematics > Biology, life sciences > Molecular biology Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematical modelling Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	1-4822-5859-5
Barcode:	9781482258592

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