Statistical Modeling and Machine Learning for Molecular Biology
The feel-good place to buy books
Statistical Modeling and Machine Learning for Molecular Biology by Alan Moses
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.
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.
| SKU | Unavailable |
| ISBN 13 | 9781482258592 |
| ISBN 10 | 1482258595 |
| Title | Statistical Modeling and Machine Learning for Molecular Biology |
| Author | Alan Moses |
| Series | Chapman And Hall Crc Computational Biology Series |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Taylor & Francis Inc |
| Year published | 2016-12-15 |
| Number of pages | 264 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |