Data Mining and Applications in Genomics

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 systema...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Ao, Sio-Iong (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Dordrecht : Springer Netherlands : Imprint: Springer, 2008.
Edición:1st ed. 2008.
Colección:Lecture Notes in Electrical Engineering, 25
Temas:
Data mining.
Medical genetics.
Bioinformatics.
Electronics.
Data Mining and Knowledge Discovery.
Medical Genetics.
Computational and Systems Biology.
Electronics and Microelectronics, Instrumentation.
Acceso en línea:Texto Completo
Descripción
Sumario: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.
Descripción Física:XII, 152 p. online resource.
ISBN:9781402089756
ISSN:1876-1119 ;

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