Applying knowledge-anchored hypothesis discovery methods to advance clinical and translational research: the OAMiner project |
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| Authors: | Philip R O Payne Rebecca D Jackson Thomas M Best Tara B Borlawsky Albert M Lai Stephen James Metin N Gurcan |
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| Affiliation: | 1.Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio, USA;2.Department of Internal Medicine, The Ohio State University, Columbus, Ohio, USA;3.Department of Family Medicine, The Ohio State University, Columbus, Ohio, USA |
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| Abstract: | 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. |
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| Keywords: | Informatics, computing methodologies, knowledge bases, research design, phenotype, biological markers, visualization of data and knowledge, translational research— application of biological knowledge to clinical care, linking the genotype and phenotype, methods for integration of information from disparate sources, knowledge acquisition and knowledge management, skeletal muscle, cartilage, osteoarthritis, data modeling and integration, knowledge representations, data models, imaging informatics, image analysis, CAD, radiology, pathology |
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