Data integration and analysis for mapping malaria parasite traits

Information

  • Research Project
  • 10216644
  • ApplicationId
    10216644
  • Core Project Number
    P01AI127338
  • Full Project Number
    5P01AI127338-05
  • Serial Number
    127338
  • FOA Number
    PAR-16-413
  • Sub Project Id
    6013
  • Project Start Date
    8/1/2017 - 6 years ago
  • Project End Date
    7/31/2022 - a year ago
  • Program Officer Name
  • Budget Start Date
    8/1/2021 - 2 years ago
  • Budget End Date
    7/31/2022 - a year ago
  • Fiscal Year
    2021
  • Support Year
    05
  • Suffix
  • Award Notice Date
    7/26/2021 - 2 years ago
Organizations

Data integration and analysis for mapping malaria parasite traits

ABSTRACT The ability to conduct targeted genetic crosses in malaria provides exciting opportunities to uncover genetic mechanisms linked to drug resistance. Core B will provide a centralized resource for all project data, standardized bioinformatics analysis, the integrated, network-based analysis required by RP02 and RP03. All of these data and results will then be deposited in relevant public resources. Extensive ?omics data will be collected for each progeny clone (i.e., transcripts, proteins and metabolites) and deposited in public archives by Core C. Because such data from the large numbers of unique recombinant progeny provided by Core A/RP01 are more powerful when integrated, Core B will maintain the required computational infrastructure to standardize project metadata and link genotypes to collected phenotypes. In tandem with RP02, Core B serves as the focal point of all project data. Because our efforts will also generate specialized metadata for which no standard archives exist, we will work closely with EuPathDB to ensure timely and relevant community access of all Project data. Providing standard analysis and significant hardware resources will also open up new avenues of integrated data analysis within the Project, which in turn will be shared via EuPathDB. Further, these significant, metadata- labeled collections of data will provide an extremely rich resource for bioinformaticians and computational biologists. Although publically available datasets of this scope and size are only available for cancer biology, they have been invaluable in the development of computational methods, e.g., predicting drug combination efficiency. We imagine our resource would be just as popular and recruit many participants to improve prediction of drug responses and other biological traits in malaria parasites. In addition to a letter of support from EupathDB on community access, we also include a letter from African researchers who are already highly interested in this data resource.

IC Name
NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES
  • Activity
    P01
  • Administering IC
    AI
  • Application Type
    5
  • Direct Cost Amount
    121804
  • Indirect Cost Amount
    66383
  • Total Cost
  • Sub Project Total Cost
    188187
  • ARRA Funded
    False
  • CFDA Code
  • Ed Inst. Type
  • Funding ICs
    NIAID:188187\
  • Funding Mechanism
    Non-SBIR/STTR RPGs
  • Study Section
    ZAI1
  • Study Section Name
    Special Emphasis Panel
  • Organization Name
    UNIVERSITY OF NOTRE DAME
  • Organization Department
  • Organization DUNS
    824910376
  • Organization City
    NOTRE DAME
  • Organization State
    IN
  • Organization Country
    UNITED STATES
  • Organization Zip Code
    465565708
  • Organization District
    UNITED STATES