• DocumentCode
    3410045
  • Title

    Labeling and enhancing life sciences links

  • Author

    Heymann, S. ; Naumann, F. ; Raschid, L. ; Rieger, P.

  • Author_Institution
    University of Maryland
  • fYear
    2004
  • fDate
    19-19 Aug. 2004
  • Firstpage
    569
  • Lastpage
    570
  • Abstract
    Life sciences data sources contain data about scientific objects such as genes and sequences that are richly interconnected, i.e., a gene object may have links to sequences, proteins, SNPs, citations, etc. Scientific knowledge is enhanced by exploration of relationships between scientific objects, requiring traversal of both links and paths (informally concatenations of links). There are significant limitations and challenges of such exploration, because the links are inherently poor with respect to syntactic representation and semantic knowledge. The links are syntactically poor because the source
  • Keywords
    Algorithm design and analysis; Bioinformatics; Data models; Database languages; Diseases; HTML; Humans; Labeling; Performance analysis; Proteins;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Systems Bioinformatics Conference, 2004. CSB 2004. Proceedings. 2004 IEEE
  • Conference_Location
    Stanford, CA, USA
  • Print_ISBN
    0-7695-2194-0
  • Type

    conf

  • DOI
    10.1109/CSB.2004.1332512
  • Filename
    1332512