Bibliographical noteKAUST Repository Item: Exported on 2023-05-26
Acknowledgements: This work was primarily supported by funding from the National Library of Medicine (NLM T15LM009451 and T15LM007079) to T.J.C. and in part by the National Center for Advancing Translational Sciences (NCATS U24TR002306) to M.A.H. and P.N.R., the National Human Genome Research Institute (NHGRI 5RM1HG010860) to M.A.H., P.N.R., N.A.V., and N.A.M., the NLM (R01LM013400) to L.E.H. and (R01LM006910) G.H., the Medical Research Council (MR/P02002X/1) to J.H.C., the National Heart, Lung, and Blood Institute (NHLBI 1K23HL161352) to K.E.T., the NHGRI (5U24HG011449-02) to P.N.R., and the Intramural Research Program of the NHGRI (ZIA HG200417) to J.C.D. and C.Z. The authors thank colleagues at the Health Data Compass warehouse, Children’s Hospital Colorado Research Informatics team, and the OMOP2OBO and Machine Learning Working Groups at the National COVID Cohort Collaboration for piloting testing, extending, and improving the mappings. The authors would also like to thank Drs. Paul Schofield (University of Oxford) and members of Dr. Robert Hoehndorf’s (King Abdullah University of Science and Technology) lab for their feedback on the mappings.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.