• DocumentCode
    3144491
  • Title

    Toward a systems biology software toolkit

  • Author

    Johann, Donald J. ; McGuigan, Michael D. ; Tomov, Stanmire ; Blum, Eric ; Whiteley, Gordon R. ; Petricoin, Emanuel F. ; Liotta, Lance A.

  • Author_Institution
    Nat. Inst. of Health, Bethesda, MD, USA
  • fYear
    2004
  • fDate
    24-25 June 2004
  • Firstpage
    500
  • Lastpage
    505
  • Abstract
    Insight to complex problems may be revealed when domain data sets are viewed or structured in new and innovative ways. Systems approaches to biomedical problems fundamentally involve forecasting, and a deliberate integration of diverse data sources. Adding a clinical proteomic dimension to these developing efforts affirms the ultimate aims of enhanced diagnostic prediction, maximizing the possibility for a rational therapy individualized to a patient´s pathologic process, and thus, improving patient outcomes. Consistent with these evolving goals, computer-aided diagnostic systems are rapidly approaching a new paradigm involving the integration of medical imaging with high throughput molecular medicine tests. As medical imaging systems become more sensitive in finding anatomic anomalies, their lack of specificity becomes much more of a clinical dilemma. Proteomic tests may be used to help resolve the lack of specificity of imaging findings. A synergistic test composed of a targeted imaging study correlated with a genomic or proteomic test(s), offers the potential of a tremendous medical advancement. Bioinformatic software toolkits are crucial components of these systems. Open source software provides a mechanism for leveraging existing toolkits, sharing expertise, accelerating development, and furthering biomedical, software, and systems sciences in new and complex multi-disciplinary fields. Our evolving toolkit utilizes components from several existing open source projects. It will initially be customized for serum proteomic pattern diagnostics, which will be used in the upcoming NCI/CCR Clinical Trial involving the monitoring for ovarian cancer recurrence.
  • Keywords
    biology computing; medical diagnostic computing; open systems; anatomic anomalies; clinical proteomic dimension; complex problems; computer-aided diagnostic systems; enhanced diagnostic prediction; genomic tests; imaging findings specificity; medical imaging; open source software; proteomic tests; rational therapy; systems biology software toolkit; targeted imaging study; Bioinformatics; Biomedical imaging; Medical diagnostic imaging; Medical tests; Medical treatment; Open source software; Proteomics; Software systems; Software tools; Systems biology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer-Based Medical Systems, 2004. CBMS 2004. Proceedings. 17th IEEE Symposium on
  • ISSN
    1063-7125
  • Print_ISBN
    0-7695-2104-5
  • Type

    conf

  • DOI
    10.1109/CBMS.2004.1311764
  • Filename
    1311764