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Computational Biology and Bioinformatics
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Computational Biology and Bioinformatics : Gene Regulation

Book Details

Format Hardback or Cased Book
ISBN-10 1498724973
ISBN-13 9781498724975
Publisher Taylor & Francis Inc
Imprint CRC Press Inc
Country of Manufacture US
Country of Publication GB
Publication Date May 9th, 2016
Print length 438 Pages
Weight 800 grams
Dimensions 24.30 x 16.20 x 2.90 cms
Product Classification: Biology, life sciencesComputer science
Ksh 36,000.00
Werezi Extended Catalogue 0 in stock

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This book presents the latest research in computational biology and bioinformatics, with a thematic focus on gene regulation. It is designed to be self-contained and comprehensive, targeting senior undergraduates and junior graduate students in the related disciplines such as bioinformatics, computational biology, biostatistics, genome science, computer science, applied data mining, applied machine learning, life science, biomedical science, and genetics. In addition, this book serves as a useful reference for both bioinformaticians and computational biologists.

The advances in biotechnology such as the next generation sequencing technologies are occurring at breathtaking speed. Advances and breakthroughs give competitive advantages to those who are prepared. However, the driving force behind the positive competition is not only limited to the technological advancement, but also to the companion data analytical skills and computational methods which are collectively called computational biology and bioinformatics. Without them, the biotechnology-output data by itself is raw and perhaps meaningless. To raise such awareness, we have collected the state-of-the-art research works in computational biology and bioinformatics with a thematic focus on gene regulation in this book.

This book is designed to be self-contained and comprehensive, targeting senior undergraduates and junior graduate students in the related disciplines such as bioinformatics, computational biology, biostatistics, genome science, computer science, applied data mining, applied machine learning, life science, biomedical science, and genetics. In addition, we believe that this book will serve as a useful reference for both bioinformaticians and computational biologists in the post-genomic era.


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