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: Mathematica for Bioinformatics
    sub title: A Wolfram Language Approach to Omics
  name:
    name part: Mias, George.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2018
    edition: 1st ed. 2018.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVI, 384 p. 175 illus., 156 illus. in color. online resource.
  abstract: This book offers a comprehensive introduction to using Mathematica and the Wolfram Language for Bioinformatics. The chapters build gradually from basic concepts and the introduction of the Wolfram Language and coding paradigms in Mathematica, to detailed worked examples derived from typical research applications using Wolfram Language code. The coding examples range from basic sequence analysis, accessing genomic databases, and differential gene expression, to time series analysis of longitudinal omics experiments, multi-omics integration and building dynamic interactive bioinformatics tools using the Wolfram Language. The topics address the daily bioinformatics needs of a broad audience: experimental users looking to understand and visualize their data, beginner bioinformaticians acquiring coding expertise in providing biological research solutions, and practicing expert bioinformaticians working on omics who wish to expand their toolset to include the Wolfram Language.
  table of contents: 1 Introduction to Bioinformatics -- 2. A Mathematica Primer for Bioinformaticians -- 3. Statistics for Genomic Analysis -- 4. Genomic Sequences -- 5. Databases -- 6. Transcriptomics -- 7. Proteomics -- 8. Metabolomics -- 9. Systems Biology -- 10. Networks -- 11. Time Series Analysis -- 12. Omics Integration and Systems Medicine -- 13. Bioinformatics Development with Mathematica.
  note: by George Mias.
  subject:
    topic: Bioinformatics
  subject:
    topic: Computational biology
  subject:
    topic: Metabolism
  subject:
    topic: Microarrays
  subject:
    topic: Systems biology
  subject:
    topic: Bioinformatics
  subject:
    topic: Biostatistics
  subject:
    topic: Computer Appl. in Life Sciences
  subject:
    topic: Metabolomics
  subject:
    topic: Microarrays
  subject:
    topic: Systems Biology
  subject:
    topic: Computational Biology/Bioinformatics
  subject:
    topic: Biostatistics
  classification: QH324.2-324.25
  classification: 570.285
  related item:
    title info:
      title: Springer eBooks
  identifier: 9783319723778
  identifier: https://doi.org/10.1007/978-3-319-72377-8
  record info:
    record creation date: 180316
    record change date: 20191220125823.0
    record identifier: 978-3-319-72377-8