Ontology-anchored Approaches to Conceptual Knowledge Discovery in a Multi-dimensional Research Data Repository

Abstract

Chronic Lymphocytic Leukemia (CLL) is the most common adult leukemia in the U.S., and is currently incurable. Though a small number of biomarkers that may correlate to risk of disease progression or treatment outcome in CLL have been discovered, few have been validated in prospective studies or adopted in clinical practice. In order to address this gap in knowledge, it is desirable to discover and test hypotheses that are concerned with translational biomarker-to-phenotype correlations. We report upon a study in which commonly available ontologies were utilized to support the discovery of such translational correlations. We have specifically applied a technique known as constructive induction to reason over the contents of a research data repository utilized by the NCI-funded CLL Research Consortium. Our findings indicate that such an approach can produce semantically meaningful results that can inform hypotheses about higher-level relationships between the types of data contained in such a repository.

Figure 1:

Constructive induction methodology.

Figure 2:

Overview of study methods