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Statistical Modeling and Machine Learning for Molecular Biology (Chapman & Hall/CRC Computational Biology Series) - Hardcover
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.
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- PublisherChapman and Hall/CRC
- Publication date2017
- ISBN 10 1138407216
- ISBN 13 9781138407213
- BindingHardcover
- LanguageEnglish
- Edition number1
- Number of pages280
- Rating
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Statistical Modeling and Machine Learning for Molecular Biology (Chapman & Hall/Crc Mathematical and Computational Biology)
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Chapman and Hall/CRC 2017-07-03, 2017
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