Background: Most of earlier studies in the field of literature-based discovery have adopted Swanson’s ABC model that links pieces of knowledge entailed in disjoint literatures. However, the issue concerning their practicability remains to be solved since most of them did not deal with the context surrounding the discovered associations and usually not accompanied with clinical confirmation. In this study, we aim to propose a method that expands and elaborates the existing hypothesis by advanced text mining techniques for capturing contexts. We extend ABC model to allow for multiple B terms with various biological types. Results: We were able to concretize a specific, metabolite-related hypothesis with abundant contextual information by using the proposed method. Starting from explaining the relationship between lactosylceramide and arterial stiffness, the hypothesis was extended to suggest a potential pathway consisting of lactosylceramide, nitric oxide, malondialdehyde, and arterial stiffness. The experiment by domain experts showed that it is clinically valid. Conclusions: The proposed method is designed to provide plausible candidates of the concretized hypothesis, which are based on extracted heterogeneous entities and detailed relation information, along with a reliable ranking criterion. Statistical tests collaboratively conducted with biomedical experts provide the validity and practical usefulness of the method unlike previous studies. Applying the proposed method to other cases, it would be helpful for biologists to support the existing hypothesis and easily expect the logical process within it.
Bibliographical noteFunding Information:
This work was supported by the Bio-Synergy Research Project (NRF-2013M3A9C 4078138, NRF-2012M3A9C4048762) of the Ministry of Science, ICT and Future Planning through the National Research Foundation. The authors who were funded are MS, JHL, and SHB. This work was supported by the Bio-Synergy Research Project (NRF-2013M3A9C4078138, NRF-2012M3A9C4048762) of the Ministry of Science, ICT and Future Planning through the National Research Foundation.
All Science Journal Classification (ASJC) codes
- Biochemistry, Genetics and Molecular Biology(all)
- Agricultural and Biological Sciences(all)