Statistical Modeling and Machine Learning for Molecular Biology
by
Alan Moses
Book Details
Format
Paperback / Softback
Book Series
Chapman & Hall/CRC Computational Biology Series
ISBN-10
1482258595
ISBN-13
9781482258592
Publisher
Taylor & Francis Inc
Imprint
Chapman & Hall/CRC
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Dec 15th, 2016
Print length
264 Pages
Weight
434 grams
Dimensions
23.60 x 15.70 x 1.90 cms
Product Classification:
Mathematical modellingMolecular biologyMachine learning
Ksh 11,350.00
Werezi Extended Catalogue
Delivery in 28 days
Delivery Location
Delivery fee: Select location
Delivery in 28 days
Secure
Quality
Fast
The book covers several of the major data analysis techniques used to analyze data from high-throughput molecular biology and genomics experiments. It also explains the major concepts behind most of the popular techniques and examines some of the simpler techniques in detail.
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.
Get Statistical Modeling and Machine Learning for Molecular Biology by at the best price and quality guaranteed only at Werezi Africa's largest book ecommerce store. The book was published by Taylor & Francis Inc and it has pages.
