Towards Improving the Efficiency of Drug Repurposing by Leveraging Node Promiscuity in Biomedical Knowledge Graphs
Authors: 
Daniel Korn, Pei-Yu Hou, Kara Schatz, Jon-Michael Beasley, Alexander Tropsha, Rada ChirkovaAuthors Info & Claims
Article No.: 8, Pages 1 - 32
Abstract
To accelerate the time- and labor-intensive processes of drug discovery and repurposing, it is increasingly common to mine knowledge sources for connections between diseases and the drugs that can treat them. In this article we address the scalability challenge in the connection mining, by introducing algorithms that can be used to find plausible mechanistic connections between drugs and the potentially associated diseases in biomedical knowledge graphs. These connections are then presented to biomedical experts as candidate hypotheses for further studies of whether the drugs can be repurposed to treat the diseases.
One challenge that has to be addressed in this effort is the processing of promiscuous knowledge-graph nodes, that is, nodes associated with numerous relationships that may not be unique or indicative of the node properties. As it turns out, the multiplicity of relationships involving promiscuous graph nodes may prevent the aforementioned path-finding algorithms from aiding in drug repurposing. To address the promiscuous-node challenge, we introduce promiscuity scores for nodes and paths in knowledge graphs, and incorporate the scores in the proposed path-finding algorithms. We report experimental results that indicate that paths with low-promiscuity scores could be meaningful and of interest to biomedical experts in drug repurposing.
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- Towards Improving the Efficiency of Drug Repurposing by Leveraging Node Promiscuity in Biomedical Knowledge Graphs
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Publication History
Published: 09 January 2025
Online AM: 09 December 2024
Accepted: 19 November 2024
Revised: 13 November 2024
Received: 31 May 2023
Published in HEALTH Volume 6, Issue 1
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