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.
| ISBN: | 9781138407213 |
| Publication date: | 27th July 2017 |
| Author: | Alan Moses |
| Publisher: | CRC Press an imprint of Taylor & Francis Ltd |
| Format: | Hardback |
| Pagination: | 280 pages |
| Series: | Chapman & Hall/CRC Computational Biology Series |
| Genres: |
Probability and statistics Biology, life sciences |
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.
Statistical Modeling and Machine Learning for Molecular Biology features in the following genres: Probability and statistics, Biology, life sciences
Hardback, Ebook, Paperback. £189.00, down from the £210.00 cover price. Not Available.
Statistical Modeling and Machine Learning for Molecular Biology was written by Alan Moses and published by CRC Press an imprint of Taylor & Francis Ltd
Statistical Modeling and Machine Learning for Molecular Biology has 280 pages
Yes it is part of Chapman & Hall/CRC Computational Biology Series series
£189.00, reduced from £210.00. Not Available.