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| Funder | NATIONAL INSTITUTE OF DENTAL & CRANIOFACIAL RESEARCH |
|---|---|
| Recipient Organization | University of Southern California |
| Country | United States |
| Start Date | Aug 15, 2024 |
| End Date | May 31, 2029 |
| Duration | 1,750 days |
| Number of Grantees | 2 |
| Roles | Co-Investigator; Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10976285 |
PROJECT ABSTRACT Dental, Oral and Craniofacial health (DOC) plays a significant factor in the overall well-being of the population. About half of all birth defects are associated with craniofacial malformations. Many other genetic conditions manifest themselves via phenotypes in the face and skull and are
associated with communication disorders, neurological development and other factors. Furthermore, oral health plays a significant role in overall human health. Driven by the importance of DOC research to overall human health, the National Institute of Dental and Craniofacial Research (NIDCR) established the FaceBase Consortium in 2009 to
advance research relevant to the NIDCR mission by creating comprehensive datasets of craniofacial development and dysmorphologies in order to disseminate these datasets to the wider craniofacial research community and support reuse of data for new research projects and collaborations. SInce its creation, FaceBase has become a central data repository resource
funded for diverse dental and craniofacial researchers. We propose to build on the success of FaceBase to date to 1) expand our inclusive community outreach, training, and education resources by fostering an active and diverse community of users across the translational spectrum of Dental, Oral and Craniofacial (DOC) and related
disciplines trained in use of FaceBase, 2) enhance FaceBase services to efficiently serve a growing community ranging from single investigators to multi-consortia, and empower scientists across the translational spectrum of DOC research and other relevant health studies to advice their research using FAIR, TRUSTworthy, scientifically robust, data-driven, and AI/ML/DL-ready
resources, and 3) build on our robust and agile project management structure to meet the new requirements of the extended use cases and community envisioned by this proposal.
University of Southern California
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