GPU-accelerated Peptide Search

Information

  • Research Project
  • 8201122
  • ApplicationId
    8201122
  • Core Project Number
    R43HG006414
  • Full Project Number
    1R43HG006414-01
  • Serial Number
    6414
  • FOA Number
    PA-10-050
  • Sub Project Id
  • Project Start Date
    8/12/2011 - 13 years ago
  • Project End Date
    7/31/2013 - 11 years ago
  • Program Officer Name
    BONAZZI, VIVIEN
  • Budget Start Date
    8/12/2011 - 13 years ago
  • Budget End Date
    7/31/2013 - 11 years ago
  • Fiscal Year
    2011
  • Support Year
    1
  • Suffix
  • Award Notice Date
    8/11/2011 - 13 years ago
Organizations

GPU-accelerated Peptide Search

DESCRIPTION (provided by applicant): The use of Graphics Processing Unit (GPU) devices is proposed to increase the speed of peptide search by as much as an order of magnitude. Peptide search engines perform the most computation-intensive task in shotgun proteomics. This proposal is to speed up peptide search using the increasingly popular approach of general-purpose computation on highly-parallel GPU devices. Computation using GPUs to gain "desktop supercomputer" performance at low cost is an active and fruitful area of research. This project will obtain these benefits for peptide search. As a result, researchers will be able to take experiments that today must be analyzed on a computer cluster, and instead analyze them on their desktop computer. PUBLIC HEALTH RELEVANCE: A enhancement to the popular peptide search engine X!Tandem is proposed, to allow it to run in parallel on graphics processing unit (GPU) cards with dramatically faster performance. This will allow much faster and less-expensive operation, allowing proteomics researchers to analyze large proteomics experiments or search for post- translational modifications (PTMs) using their existing desktop computer. Proteomics has led to many important advances in biological understanding. Yet, many valuable data sets are not searched for PTMs, simply because the computer power necessary to conduct the searches is not available. With this project, we plan to substantially reduce the computational cost of proteomics experiments, via a peptide search engine making use of inexpensive, highly parallel GPU hardware. Thus, this project, if successful, will allow proteomics to be more successfully exploited for public health. The research team is well-qualified to undertake this research, having extensive, direct experience in all the scientific disciplines and specific software elements necessary. The research team includes experts in proteomics, mass spectrometry, peptide search, and GPU computing.

IC Name
NATIONAL HUMAN GENOME RESEARCH INSTITUTE
  • Activity
    R43
  • Administering IC
    HG
  • Application Type
    1
  • Direct Cost Amount
  • Indirect Cost Amount
  • Total Cost
    203600
  • Sub Project Total Cost
  • ARRA Funded
    False
  • CFDA Code
    172
  • Ed Inst. Type
  • Funding ICs
    NHGRI:203600\
  • Funding Mechanism
    SBIR-STTR
  • Study Section
    ZRG1
  • Study Section Name
    Special Emphasis Panel
  • Organization Name
    INSILICOS
  • Organization Department
  • Organization DUNS
    126643241
  • Organization City
    SEATTLE
  • Organization State
    WA
  • Organization Country
    UNITED STATES
  • Organization Zip Code
    981094955
  • Organization District
    UNITED STATES