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: Bioinformatics Using Computational Intelligence Paradigms
  name:
    name part: Seiffert, Udo.
    role:
      role term: editor.
  name:
    name part: Jain, Lakhmi C.
    role:
      role term: editor.
  name:
    name part: Schweizer, Patric.
    role:
      role term: editor.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2005
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: VII, 211 p. online resource.
  abstract: Bioinformatics as well as Computational Intelligence are undoubtedly remarkably fast growing fields of research and real-world applications with enormous potential for current and future developments. "Bioinformatics using Computational Intelligence Paradigms" contains recent theoretical approaches and guiding applications of biologically inspired information processing systems(Computational Intelligence) against the background of bioinformatics. This carefully edited monograph combines the latest results of Bioinformatics and Computational Intelligence and offers a promising cross-fertilisation and interdisciplinary work between these growing fields.
  table of contents: Medical Bioinformatics: Detecting Molecular Diseases with Case-Based Reasoning -- Prototype Based Recognition of Splice Sites -- Contact Based Image Compression in Biomedical High-Throughput Screening Using Artificial Neural Networks -- Discriminative Clustering of Yeast Stress Response -- A Dynamic Model of Gene Regulatory Networks Based on Inertia Principle -- Class Prediction with Microarray Datasets -- Random Voronoi Ensembles for Gene Selection in DNA Microarray Data -- Cancer Classification with Microarray Data Using Support Vector Machines -- Artificial Neural Networks for Reducing the Dimensionality of Gene Expression Data.
  note: edited by Udo Seiffert, Lakhmi C. Jain, Patric Schweizer.
  subject:
    topic: Computer science
  subject:
    topic: Biotechnology
  subject:
    topic: Computers
  subject:
    topic: Artificial intelligence
  subject:
    topic: Bioinformatics
  subject:
    topic: Applied mathematics
  subject:
    topic: Engineering mathematics
  subject:
    topic: Computational intelligence
  subject:
    topic: Computer Science
  subject:
    topic: Theory of Computation
  subject:
    topic: Computational Intelligence
  subject:
    topic: Appl.Mathematics/Computational Methods of Engineering
  subject:
    topic: Bioinformatics
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: Biotechnology
  classification: QA75.5-76.95
  classification: 004.0151
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Studies in Fuzziness and Soft Computing, 176
  identifier: 9783540323617
  identifier: http://dx.doi.org/10.1007/b13301
  record info:
    record creation date: 100805
    record change date: 20151204190152.0
    record identifier: 978-3-540-32361-7