Statistical Applications in Genetics and Molecular Biology (STAT APPL GENET MOL )

Publisher: Berkeley Electronic Press

Description

Statistical Applications in Genetics and Molecular Biology seeks to publish significant research on the application of statistical ideas to problems arising from computational biology. The focus of the papers should be on the relevant statistical issues but should contain a succinct description of the relevant biological problem being considered. The range of topics is wide and will include topics such as linkage mapping, association studies, gene finding and sequence alignment, protein structure prediction, design and analysis of microarray data, molecular evolution and phylogenetic trees, DNA topology, and data base search strategies.

  • Impact factor
    1.52
    Show impact factor history
     
    Impact factor
  • 5-year impact
    1.70
  • Cited half-life
    7.20
  • Immediacy index
    0.12
  • Eigenfactor
    0.00
  • Article influence
    0.91
  • Website
    Statistical Applications in Genetics and Molecular Biology website
  • Other titles
    Statistical applications in genetics and molecular biology, SAGMB
  • ISSN
    1544-6115
  • OCLC
    52157137
  • Material type
    Document, Periodical, Internet resource
  • Document type
    Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Berkeley Electronic Press

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • On non-commercial authors personal website, non-commercial authors open-access university and employers institutional repository and non-commercial authors course website
    • PubMed and UK PubMed after 12 months (automatic for several journals)
    • Publisher copyright and source must be acknowledged
    • Publisher's version/PDF may be used
  • Classification
    ‚Äč green