02291oam 2200469I 450 991016285740332120230612184505.01-4822-5862-51-315-37226-61-4822-5860-910.1201/9781315372266(CKB)3710000001021899(MiAaPQ)EBC4778632(OCoLC)967412430(EXLCZ)99371000000102189920180706h20172017 uy 0engrdacontentrdamediardacarrierStatistical modeling and machine learning for molecular biology /Alan Moses, University of Toronto, CanadaBoca Raton :CRC Press,[2017]©20171 online resourceChapman & Hall/CRC mathematical and computational biology series1-138-40721-6 1-4822-5859-5 section 1. Overview -- section 2. Clustering -- section 3. Regression -- section 4. Classification.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.Chapman and Hall/CRC mathematical & computational biology series.Molecular biologyStatistical methodsMolecular biologyData processingMolecular biologyStatistical methods.Molecular biologyData processing.572.8Moses Alan1212883FlBoTFGFlBoTFGBOOK9910162857403321Statistical modeling and machine learning for molecular biology2801009UNINA