Integration and analysis tools for protein interaction networks

Information

  • Research Project
  • 7155257
  • ApplicationId
    7155257
  • Core Project Number
    R43RR022659
  • Full Project Number
    1R43RR022659-01A1
  • Serial Number
    22659
  • FOA Number
    PA-06-11
  • Sub Project Id
  • Project Start Date
    9/17/2006 - 18 years ago
  • Project End Date
    8/31/2008 - 16 years ago
  • Program Officer Name
    SHEELEY, DOUGLAS
  • Budget Start Date
    9/17/2006 - 18 years ago
  • Budget End Date
    8/31/2008 - 16 years ago
  • Fiscal Year
    2006
  • Support Year
    1
  • Suffix
    A1
  • Award Notice Date
    9/17/2006 - 18 years ago
Organizations

Integration and analysis tools for protein interaction networks

[unreadable] DESCRIPTION (provided by applicant): The growing size and diversity of biological databases has necessitated the design of new scalable tools that can search across multiple databases and integrate information from multiple data sources. We propose to develop software for integrating and understanding protein-protein interactions, a fundamental problem in biology. A set of tools will be developed for constructing large-scale probabilistic networks of protein interactions using data sources such as microarrays, bioimages, GO annotations, genomic data, literature, and experimental data. The techniques will be based on Bayesian networks (BN) and Support Vector Machines (SVM), and will be made scalable to large datasets. The second goal is to develop tools for analyzing interaction networks for pathway discovery, motif finding, and function identification. These tools will be based on current research in the areas of graph algorithms, bioinformatics, machine learning, and databases. We will target two model organisms: S. cerevisiae (yeast) and C. elegans (worm). The quality of the constructed networks will be evaluated with known protein interactions for these species. Scalability tests will be performed with the worm interactome that is about ten times larger than the yeast interactome. The developed tools will be compatible with current standards and integrated into a database backend. The resulting software will enable assimilation of heterogeneous biological data with the ultimate goal of increased understanding of fundamental processes in molecular biology. The goal of this Phase I project is to prove the feasibility of constructing and analyzing probabilistic protein interaction networks in a scalable manner using new algorithms. The integration of diverse data sources such as microarrays, genomics, literature, and high-throughput experiments into pathways will facilitate the study the biological processes behind human diseases. The understanding of protein interactions within a pathway and interactions between pathways will lead to the selection of appropriate targets for therapeutic intervention, and eventually to cheaper and faster drug discovery. [unreadable] [unreadable] [unreadable] [unreadable]

IC Name
NATIONAL CENTER FOR RESEARCH RESOURCES
  • Activity
    R43
  • Administering IC
    RR
  • Application Type
    1
  • Direct Cost Amount
  • Indirect Cost Amount
  • Total Cost
    199950
  • Sub Project Total Cost
  • ARRA Funded
  • CFDA Code
    389
  • Ed Inst. Type
  • Funding ICs
    NCRR:199950\
  • Funding Mechanism
  • Study Section
    BDMA
  • Study Section Name
    Biodata Management and Analysis Study Section
  • Organization Name
    ACELOT, INC.
  • Organization Department
  • Organization DUNS
    784692001
  • Organization City
    SANTA BARBARA
  • Organization State
    CA
  • Organization Country
    UNITED STATES
  • Organization Zip Code
    931111471
  • Organization District
    UNITED STATES