Rare Disease Translational Research

• Development of natural language processing (NLP)–based approaches to systematically analyze PubMed abstracts, social media, and NIH funding pertinent to rare diseases. These analyses help identify gaps and scientific challenges that remain unaddressed in rare disease research (John, et.al., AMIA Annu Symp Proc. 2021; Zhu, et.al., Orphanet J Rare Dis. 2021; Karas B, et.al., Front. Artif. Intell. 2022; Zhu, et.al., Front. Artif. Intell. 2022; Kariampuzha, et al., J Transl Med. 2023).
• Development of a computational approach to support data harmonization and data interoperability with existing standardized terminologies and ontologies for NCATS’ Genetics and Rare Diseases (GARD) Information Center. One outcome from these efforts, the GARD Data Tree, has facilitated curation efforts (Zhu, et al., JMIR Med Inform. Oct 2020).

https://rdas.ncats.nih.gov/browser/ (neo4j)

rdas.ncats.nih.gov

To fulfill the need for integrating biomedical data in a structured, standardized and semantic way for advancing research in rare diseases, the latest research findings in the rare disease field, mined from PubMed articles, grant funding and clinical trials, have been complied to develop NCATS Rare Disease Alert System (RDAS). With RDAS, we can create alerts on research finding updates, thereby providing an up-to-date resource of information to support the rare disease clinical/research community.

https://rarediseases.info.nih.gov

The Genetic and Rare Diseases (GARD) Information Center provides the public with access to current, reliable and easy-to-understand information about rare or genetic diseases. Informatics scientists organize, synthesize and update the backbone database for GARD. The program is funded by NCATS and the National Human Genome Research Institute.