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Advanced Information and Knowledge Processing

Hierarchical Feature Selection for Knowledge Discovery

Application of Data Mining to the Biology of Ageing

Authors: Wan, Cen

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  • Discusses the state of the art in hierarchical feature selection algorithms
  • Reviews the applications of hierarchical feature selection algorithms to bioinformatics databases
  • Surveys the applications of hierarchical feature selection algorithms to research on the biology of ageing
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  • ISBN 978-3-319-97919-9
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About this book

This book is the first work that systematically describes the procedure of data mining and knowledge discovery on Bioinformatics databases by using the state-of-the-art hierarchical feature selection algorithms. The novelties of this book are three-fold. To begin with, this book discusses the hierarchical feature selection in depth, which is generally a novel research area in Data Mining/Machine Learning. Seven different state-of-the-art hierarchical feature selection algorithms are discussed and evaluated by working with four types of interpretable classification algorithms (i.e. three types of Bayesian network classification algorithms and the k-nearest neighbours classification algorithm). Moreover, this book discusses the application of those hierarchical feature selection algorithms on the well-known Gene Ontology database, where the entries (terms) are hierarchically structured. Gene Ontology database that unifies the representations of gene and gene products annotation provides the resource for mining valuable knowledge about certain biological research topics, such as the Biology of Ageing. Furthermore, this book discusses the mined biological patterns by the hierarchical feature selection algorithms relevant to the ageing-associated genes. Those patterns reveal the potential ageing-associated factors that inspire future research directions for the Biology of Ageing research.

About the authors

Dr. Cen Wan is a Postdoctoral Research Associate in the Department of Computer Science at University College London, and in the Biomedical Data Science Laboratory at The Francis Crick Institute, London, UK.

Table of contents (8 chapters)

Table of contents (8 chapters)

Buy this book

eBook n/a
  • ISBN 978-3-319-97919-9
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
Hardcover n/a
  • ISBN 978-3-319-97918-2
  • Free shipping for individuals worldwide
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Bibliographic Information

Bibliographic Information
Book Title
Hierarchical Feature Selection for Knowledge Discovery
Book Subtitle
Application of Data Mining to the Biology of Ageing
Authors
Series Title
Advanced Information and Knowledge Processing
Copyright
2019
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-319-97919-9
DOI
10.1007/978-3-319-97919-9
Hardcover ISBN
978-3-319-97918-2
Series ISSN
1610-3947
Edition Number
1
Number of Pages
XIV, 120
Number of Illustrations
29 b/w illustrations, 23 illustrations in colour
Topics