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: Network Inference in Molecular Biology
    sub title: A Hands-on Framework
  name:
    name part: Lingeman, Jesse M.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Shasha, Dennis.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2012
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: IX, 100 p. 58 illus. online resource.
  abstract: Inferring gene regulatory networks is a difficult problem to solve due to the relative scarcity of data compared to the potential size of the networks. While researchers have developed techniques to find some of the underlying network structure, there is still no one-size-fits-all algorithm for every data set. Network Inference in Molecular Biology examines the current techniques used by researchers, and provides key insights into which algorithms best fit a collection of data. Through a series of in-depth examples, the book also outlines how to mix-and-match algorithms, in order to create one tailored to a specific data situation. Network Inference in Molecular Biology is intended for advanced-level students and researchers as a reference guide. Practitioners and professionals working in a related field will also find this book valuable.
  table of contents: The Gene Network Inference Problem -- Experimental Inputs -- Running Examples -- Overall Workflow of Inference -- Sample Pipelines -- Roll Your Own Pipeline -- Appendix.
  note: by Jesse M. Lingeman, Dennis Shasha.
  subject:
    topic: Computer science
  subject:
    topic: Algorithms
  subject:
    topic: Bioinformatics
  subject:
    topic: Computer Science
  subject:
    topic: Computational Biology/Bioinformatics
  subject:
    topic: Bioinformatics
  subject:
    topic: Algorithm Analysis and Problem Complexity
  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: 9781461431138
  identifier: http://dx.doi.org/10.1007/978-1-4614-3113-8
  record info:
    record creation date: 120523
    record change date: 20151204180638.0
    record identifier: 978-1-4614-3113-8