rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Data Mining and Applications in Genomics
  name:
    name part: Ao, Sio-Iong.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: ne
    date issued: 2008
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XII, 152 p. online resource.
  abstract: 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.
  table of contents: Data Mining Algorithms -- Advances in Genomic Experiment Techniques -- Case Study I: Hierarchical Clustering and Graph Algorithms for Tag-SNP Selection -- Case Study II: Constrained Unidimensional Scaling for Linkage Disequilibrium Maps -- Case Study III: Hybrid PCA-NN Algorithms for Continuous Microarray Time Series -- Discussions and Future Data Mining Projects.
  note: by Sio-Iong Ao.
  subject:
    topic: Computer science
  subject:
    topic: Human genetics
  subject:
    topic: Data mining
  subject:
    topic: Bioinformatics
  subject:
    topic: Electronics
  subject:
    topic: Microelectronics
  subject:
    topic: Computer Science
  subject:
    topic: Data Mining and Knowledge Discovery
  subject:
    topic: Human Genetics
  subject:
    topic: Computational Biology/Bioinformatics
  subject:
    topic: Bioinformatics
  subject:
    topic: Electronics and Microelectronics, Instrumentation
  classification: QA76.9.D343
  classification: 006.312
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes in Electrical Engineering, 25
  identifier: 9781402089756
  identifier: http://dx.doi.org/10.1007/978-1-4020-8975-6
  record info:
    record creation date: 100301
    record change date: 20151121051955.0
    record identifier: 978-1-4020-8975-6