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| Funder | NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES |
|---|---|
| Recipient Organization | University of California, San Diego |
| Country | United States |
| Start Date | May 19, 2023 |
| End Date | Apr 30, 2028 |
| Duration | 1,808 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10844352 |
Global proteomics mass spectrometry data sharing infrastructure - Project Summary Technological developments and the increased pace of data generation in mass spectrometry (MS) now enable systematic probing of the human proteome, thus contributing to the characterization of biomolecular mechanisms required for the development of therapeutic responses to disease. Recognizing the scientific necessity of open
data to enable new discoveries and to establish the reliability of published results, the proteomics community embraced data sharing as a common practice. The authors of thousands of papers have already publicly re- leased the underlying MS data using the resources that we propose to support and extend: the MassIVE repos-
itory of mass spectrometry data and the ProteomeCentral data portal for the global ProteomeXchange consor- tium of MS data repositories. In this project, we propose to develop new proteomics MS data infrastructure, standards, workflows and data indexes to substantially advance FAIR (Findable, Accessible, Interoperable and
Reusable) access to proteomics MS datasets. First, we will develop new community standards for representation of dataset metadata and for the detailed description of proteomics identifications and abundances detected in available datasets, including peptides, proteins, isoforms and post-translational modifications. We will also ex-
tend workflows for dataset submission, processing and indexing to enable advanced queries by each dataset’s detected proteomics identifications. Second, we will create new infrastructure for researchers to share controlled access proteomics datasets from studies of human subjects where there may exist a significant risk of the data
being identifiable. Third, we will extend the ProteomeCentral data portal to support the new dataset structures, metadata and indexes allowing for the global integration of the new levels of information across all Proteo- meXchange repositories.
University of California, San Diego
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