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: Computational Cancer Biology
    sub title: An Interaction Network Approach
  name:
    name part: Vidyasagar, Mathukumalli.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxk
    date issued: 2012
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XII, 80 p. 11 illus. in color. online resource.
  abstract: This brief introduces readers to various problems in cancer biology that are amenable to analysis using methods of probability theory and statistics, building on only a basic background in these two topics. Aside from providing a self-contained introduction to several aspects of basic biology and to cancer, as well as to the techniques from statistics most commonly used in cancer biology, the brief describes several methods for inferring gene interaction networks from expression data, including one that is reported for the first time in the brief. The application of these methods is illustrated on actual data from cancer cell lines. Some promising directions for new research are also discussed. After reading the brief, engineers and mathematicians should be able to collaborate fruitfully with their biologist colleagues on a wide variety of problems.
  table of contents: Introduction -- Inferring Genetic Regulatory Networks -- Context-specific Genomic Networks -- Analyzing Statistical Significance -- Separating Drivers from Passengers -- Some Research Directions.
  note: by Mathukumalli Vidyasagar.
  subject:
    topic: Computer science
  subject:
    topic: Cancer research
  subject:
    topic: Bioinformatics
  subject:
    topic: Systems biology
  subject:
    topic: Biomathematics
  subject:
    topic: Statistics
  subject:
    topic: Control engineering
  subject:
    topic: Computer Science
  subject:
    topic: Computational Biology/Bioinformatics
  subject:
    topic: Physiological, Cellular and Medical Topics
  subject:
    topic: Control
  subject:
    topic: Statistics for Life Sciences, Medicine, Health Sciences
  subject:
    topic: Systems Biology
  subject:
    topic: Cancer Research
  classification: QH324.2-324.25
  classification: 570.285
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: SpringerBriefs in Electrical and Computer Engineering
  identifier: 9781447147510
  identifier: http://dx.doi.org/10.1007/978-1-4471-4751-0
  record info:
    record creation date: 121205
    record change date: 20151031111114.0
    record identifier: 978-1-4471-4751-0