Wangler, et al. recently published an article in Genetics on NIH funding for model organism research involving Drosophila. The authors extracted grant information from NIH ExPORTER and looked for the word “Drosophila” in either the title or abstract. By this approach the authors found that NIH support for Drosophila-based research is declining.
We chose to investigate further trends in NIH support for Drosophila and other model organism research. Two groups of NIH staff used two different approaches. Our Office of Research Information Systems (ORIS) used an automated thesaurus-based text mining system which mines not only project titles and abstracts but also the specific aims contained in the application; this is the system we use to generate “Research Condition and Disease Category” (or RCDC) tables, which are publicly posted to the NIH RePORT website. In a separate effort, our Office of Portfolio Analysis (OPA) supplemented a different text mining algorithm with extensive manual curation. Both methods – the wholly automated thesaurus-based text mining approach and the manual curation supplemented text mining approach – yielded similar findings. In this blog, we will present the results of the manually curated approach. ….