Faculty Publications
Utilizing Comprehensive Biological Network to Improve Accuracy of Computational Drug Repurposing
Document Type
Conference
Keywords
biological network, drug repurposing, matrix completion, recommender systems
Journal/Book/Conference Title
Proceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine
First Page
6299
Last Page
6305
Abstract
Drug repurposing can overcome challenges associated with expensive and time-consuming drug discovery pipelines by quickly finding new uses for existing drugs. Computational drug repurposing is founded on the principle that similar drugs treat similar diseases. Thus, the research in the field has traditionally focused on defining and implementing measures of drug and disease similarities that closely resemble similarities in the observed drug pharmacological profiles and disease pathways. In this study, we incorporate comprehensive data on biological relationships and interactions to arrive at a fast and accurate method for completing the existing knowledge on drug-disease associations and, in turn, find new indications for FDA approved drugs.
Department
Department of Computer Science
Original Publication Date
1-10-2025
DOI of published version
10.1109/BIBM62325.2024.10822046
Recommended Citation
Poleksic, Aleksandar, "Utilizing Comprehensive Biological Network to Improve Accuracy of Computational Drug Repurposing" (2025). Faculty Publications. 6734.
https://scholarworks.uni.edu/facpub/6734
