Elucidating the semantics-topology trade-off for knowledge inference-based pharmacological discovery

• Published in: Journal of biomedical semantics Vol. 15; no. 1; pp. 5 - 10
• Main Authors: Sosa, Daniel N., Neculae, Georgiana, Fauqueur, Julien, Altman, Russ B.
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 01.05.2024; BioMed Central; BMC
• Subjects: Ablation; Algebraic topology; Artificial intelligence; Bias; Disease; Drug discovery; Drug Discovery - methods; Drug Repositioning - methods; Drugs; Embedding; Genes; Graphical representations; Graphs; Knowledge graphs; Knowledge inference; Knowledge representation; Medical innovations; Methods; Network topologies; Network topology; Pharmacology; Predictions; Proteins; Semantics; Technology application; Topology; United States; Knowledge inference; Network topology; Drug discovery; Semantics; Knowledge graphs

Leveraging AI for synthesizing the deluge of biomedical knowledge has great potential for pharmacological discovery with applications including developing new therapeutics for untreated diseases and repurposing drugs as emergent pandemic treatments. Creating knowledge graph representations of intera...