Abstract
With the advances in science and technology, the number of research in rare diseases has dramatically increased over the past twenty years. Systematically accessing those research projects funded by NIH would allow us to assess the current status of research, and research gaps remain in this area. Consequently, new research might be inspired to bridge the gaps. We previously developed a knowledge graph to semantically represent NIH funded rare disease research projects by analyzing project titles. To expand the use of NIH funding data, in this study we extended the previous work in two folds, 1) we applied our self-developed NLP package named NormMap to identify rare disease related projects, 2) we semantically annotated project titles and abstracts with biomedical concepts in UMLS to illustrate the project aims. With such rich information extracted from NIH funding data via semantic annotation, an updated version of the knowledge graph will be developed to advance rare disease research as the next step.
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