{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T06:30:31Z","timestamp":1786516231174,"version":"build-2736575974"},"reference-count":32,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T00:00:00Z","timestamp":1786492800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Bioinform."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>In recent years, with the diversification and expansion of drug research in the medical field, the widespread use of drugs, particularly antibiotics, has led to increased microbial resistance. Consequently, exploring potential associations between drugs and microbes has become critically important. However, traditional biological experiments are extremely expensive and time-consuming. Therefore, developing more effective computational models for predicting potential associations between microbes and drugs is both essential and challenging.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We proposed GATROF, a hybrid heterogeneous graph-based framework for microbe\u2013drug association prediction. In GATROF, by integrating multiple microbe\u2013drug\u2013disease similarity measures, we first constructed two distinct microbe\u2013drug networks. In addition, based on different features of microbes and drugs, we further constructed two novel microbe\u2013drug feature matrices. On this basis, the microbe\u2013drug networks and the constructed feature matrices were further used in a Graph Attention Network to learn complementary topology-aware representations of microbes and drugs. These GAT-derived representations were then integrated with the constructed drug-side and microbe-side feature matrices and input into a Rotation Forest classifier for final association prediction. Experimental results and case studies demonstrated that GATROF predicts microbe\u2013drug associations more accurately than existing state-of-the-art methods.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>GATROF provides a new integrated predictive framework for predicting potential microbe\u2013drug associations. By combining heterogeneous biological information, GAT-based topological representation learning, and Rotation Forest classification, GATROF may help prioritize candidate drug\u2013microbe associations for further biological validation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fbinf.2026.1871436","type":"journal-article","created":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T05:54:57Z","timestamp":1786514097000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A microbe\u2013drug association prediction model based on graph attention networks and rotation forest"],"prefix":"10.3389","volume":"6","author":[{"given":"Jing","family":"Li","sequence":"first","affiliation":[{"name":"School of Information Engineering, Hunan Vocational College of Electronic and Technology","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juncai","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Hunan Vocational College of Electronic and Technology","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qijia","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Hunan Vocational College of Electronic and Technology","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhong","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Humanities and Education, Hunan Vocational College of Electronic and Technology","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianzhi","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Hunan Vocational College of Electronic and Technology","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingmin","family":"Liang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Hunan Vocational College of Electronic and Technology","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junzhuang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Hunan Vocational College of Electronic and Technology","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongyuan","family":"Ding","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Hunan Vocational College of Electronic and Technology","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Zeng","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Hunan Vocational College of Electronic and Technology","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Wang","sequence":"additional","affiliation":[{"name":"Big Data Innovation and Entrepreneurship Education Center of Hunan Province, Changsha University","place":["Changsha, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,12]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"268","DOI":"10.1016\/j.ijid.2020.02.018","article-title":"Discovery and development of safe-in-man broad-spectrum antiviral agents","volume":"93","author":"Andersen","year":"2020","journal-title":"Int. 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