{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T13:09:19Z","timestamp":1788786559089,"version":"build-2803163510"},"reference-count":60,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T00:00:00Z","timestamp":1788739200000},"content-version":"vor","delay-in-days":6,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["RS-2023-NR077172"],"award-info":[{"award-number":["RS-2023-NR077172"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["RS-2026-25473777"],"award-info":[{"award-number":["RS-2026-25473777"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["RS-2026-25516068"],"award-info":[{"award-number":["RS-2026-25516068"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["RS-2026-25518860"],"award-info":[{"award-number":["RS-2026-25518860"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Ministry of Trade, Industry & Resources","award":["RS-2025-13642970"],"award-info":[{"award-number":["RS-2025-13642970"]}]},{"DOI":"10.13039\/100031757","name":"AIGENDRUG Co., Ltd","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100031757","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Biomedical knowledge graphs that include drugs, genes, and diseases support drug repurposing by connecting drugs to diseases through gene-mediated multi-hop paths, thereby enabling mechanism-of-action reasoning. However, deeper traversal does not necessarily improve mechanistic reasoning: long paths grow combinatorially and frequently pass through hub genes, producing irrelevant gene regulatory signals, whereas overly constrained or sparse paths may miss broader biological context. We propose Context-Aware REasoning Path (CAREPath), a knowledge graph (KG)-large language model framework inspired by depth-search and breadth-search reasoning to balance mechanistic specificity, scalability, and context recovery. The depth-search strategy constrains traversal to short disease\u2013gene\u2013drug paths, converts each path into a structured prompt, and encodes it with a biomedical language model to generate semantic path embeddings. Complementarily, the breadth-search strategy constructs entity-level mechanism-context embeddings from one-hop gene neighborhoods and enriches them through similarity-guided augmentation using pharmacologically related drugs and gene-signature-similar diseases. Across five biomedical KGs, CAREPath achieves the best area under the precision\u2013recall curve (AUPRC) in the disease cold-start setting among 18 baselines, improving performance by up to 3.6%. Additional analyses show that semantic short-path encoding contributes most to performance, while mechanism-context augmentation improves robustness under sparse path signals and strengthens gene ontology functional agreement. Case studies and recently U.S. Food and Drug Administration (FDA)-approved indications further demonstrate its practical relevance, positioning CAREPath as a framework that supplies interpretable mechanistic rationales where constrained path is available, while remaining robust when it is not. Source code is available at https:\/\/github.com\/hamppy-song\/CAREPath.<\/jats:p>","DOI":"10.1093\/bib\/bbag472","type":"journal-article","created":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T11:23:50Z","timestamp":1786361030000},"source":"Crossref","is-referenced-by-count":0,"title":["CAREPath: semantic context-aware reasoning paths with mechanism-augmented embeddings for drug repurposing"],"prefix":"10.1093","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-3199-0138","authenticated-orcid":false,"given":"Haerin","family":"Song","sequence":"first","affiliation":[{"name":"Interdisciplinary Program in Artificial Intelligence, Seoul National University , 1 Gwanak-ro, Gwanak-gu, Seoul 08826 ,","place":["Republic of Korea"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9217-8380","authenticated-orcid":false,"given":"Dongmin","family":"Bang","sequence":"additional","affiliation":[{"name":"Interdisciplinary Program in Bioinformatics, Seoul National University , 1 Gwanak-ro, Gwanak-gu, Seoul 08826 ,","place":["Republic of Korea"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4357-1850","authenticated-orcid":false,"given":"Bonil","family":"Koo","sequence":"additional","affiliation":[{"name":"Interdisciplinary Program in Bioinformatics, Seoul National University , 1 Gwanak-ro, Gwanak-gu, Seoul 08826 ,","place":["Republic of Korea"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5385-9546","authenticated-orcid":false,"given":"Sun","family":"Kim","sequence":"additional","affiliation":[{"name":"Interdisciplinary Program in Artificial Intelligence, Seoul National University , 1 Gwanak-ro, Gwanak-gu, Seoul 08826 ,","place":["Republic of Korea"]},{"name":"Interdisciplinary Program in Bioinformatics, Seoul National University , 1 Gwanak-ro, Gwanak-gu, Seoul 08826 ,","place":["Republic of 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