Scientific evidence based rare disease research discovery with research funding data in knowledge graph.
Qian ZhuÐắc-Trung NguyễnTimothy SheilsGioconda AlyeaEric SidYanji XuJames DickensEwy A MathéAnne PariserPublished in: Orphanet journal of rare diseases (2021)
We developed an integrative knowledge graph with rare disease funding data and demonstrated its use as a source from where we can effectively identify and generate scientific evidence to support rare disease research. With the success of this preliminary study, we plan to implement advanced computational approaches for analyzing more funding related data, e.g., project abstracts and PubMed article abstracts, and linking to other types of biomedical data to perform more sophisticated research gap analysis and identify opportunities for future research in rare diseases.