Data Mining and Applications in Genomics

Sio-Iong Ao

ISBN 10: 9048180406 / ISBN 13: 9789048180400

Published by Springer Netherlands, 2010

About this Item

Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. With comprehensive introductory chapter to the data mining techniquesWith detailed descriptions of some current genomic problemsWith detailed descriptions of some tailor-made data mining algorithms for specific genomic problemsWith f. Seller Inventory # 5821872

Bibliographic Details

Title: Data Mining and Applications in Genomics

Publisher: Springer Netherlands

Publication Date: 2010

Binding: Soft cover

Condition: New

About this title

Synopsis:

Data Mining and Applications in Genomics contains the data mining algorithms and their applications in genomics, with frontier case studies based on the recent and current works at the University of Hong Kong and the Oxford University Computing Laboratory, University of Oxford. It provides a systematic introduction to the use of data mining algorithms as an investigative tool for applications in genomics. Data Mining and Applications in Genomics offers state of the art of tremendous advances in data mining algorithms and applications in genomics and also serves as an excellent reference work for researchers and graduate students working on data mining algorithms and applications in genomics.

From the Back Cover:

Data Mining and Applications in Genomics contains the data mining algorithms and their applications in genomics, with frontier case studies based on the recent and current works at the University of Hong Kong and the Oxford University Computing Laboratory, University of Oxford. It provides a systematic introduction to the use of data mining algorithms as an investigative tool for applications in genomics. Topics covered include Genomic Techniques, Single Nucleotide Polymorphisms, Disease Studies, HapMap Project, Haplotypes, Tag-SNP Selection, Linkage Disequilibrium Map, Gene Regulatory Networks, Dimension Reduction, Feature Selection, Feature Extraction, Principal Component Analysis, Independent Component Analysis, Machine Learning Algorithms, Hybrid Intelligent Techniques, Clustering Algorithms, Graph Algorithms, Numerical Optimization Algorithms, Data Mining Software Comparison, Medical Case Studies, Bioinformatics Projects, and Medical Applications.

Data Mining and Applications in Genomics offers state of the art of tremendous advances in data mining algorithms and applications in genomics and also serve as an excellent reference work for researchers and graduate students working on data mining algorithms and applications in genomics.