Applying knowledge-anchored hypothesis discovery methods to advance clinical and translational research: the OAMiner project.
The conduct of clinical and translational research regularly involves the use of a variety of heterogeneous and large-scale data resources. Scalable methods for the integrative analysis of such resources, particularly when attempting to leverage computable domain knowledge in order to generate actionable hypotheses in a high-throughput manner, remain an open area of research. In this report, we describe both a generalizable design pattern for such integrative knowledge-anchored hypothesis discovery operations and our experience in applying that design pattern in the experimental context of a set of driving research questions related to the publicly available Osteoarthritis Initiative data repository. We believe that this 'test bed' project and the lessons learned during its execution are both generalizable and representative of common clinical and translational research paradigms.
Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio, USA. philip.payne@osumc.edu
Philip R O
PR
Payne
Rebecca D
RD
Jackson
Thomas M
TM
Best
Tara B
TB
Borlawsky
Albert M
AM
Lai
Stephen
S
James
Metin N
MN
Gurcan
D057225:Data Mining; D006801:Humans; D007091:Image Processing, Computer-Assisted; D051188:Knowledge Bases; D009323:Natural Language Processing; D020370:Osteoarthritis, Knee; D057170:Translational Research, Biomedical / Q000379:methods* / Q000706:statistics & numerical data; D014584:User-Computer Interface