{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T21:05:47Z","timestamp":1775077547829,"version":"3.50.1"},"reference-count":65,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2022,7,29]],"date-time":"2022-07-29T00:00:00Z","timestamp":1659052800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"National Key Research and Development Project","award":["2019YFE0109600"],"award-info":[{"award-number":["2019YFE0109600"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61871272"],"award-info":[{"award-number":["61871272"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61911530218"],"award-info":[{"award-number":["61911530218"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017607","name":"Shenzhen Fundamental Research Program","doi-asserted-by":"publisher","award":["JCYJ20190808173617147"],"award-info":[{"award-number":["JCYJ20190808173617147"]}],"id":[{"id":"10.13039\/501100017607","id-type":"DOI","asserted-by":"publisher"}]},{"name":"open project of BGIShenzhen","award":["BGIRSZ20200002"],"award-info":[{"award-number":["BGIRSZ20200002"]}]},{"name":"Guangdong Provincial Key Laboratory","award":["2020B121201001"],"award-info":[{"award-number":["2020B121201001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,9,20]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>The associations between biomarkers and human diseases play a key role in understanding complex pathology and developing targeted therapies. Wet lab experiments for biomarker discovery are costly, laborious and time-consuming. Computational prediction methods can be used to greatly expedite the identification of candidate biomarkers.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Here, we present a novel computational model named GTGenie for predicting the biomarker\u2013disease associations based on graph and text features. In GTGenie, a graph attention network is utilized to characterize diverse similarities of biomarkers and diseases from heterogeneous information resources. Meanwhile, a pretrained BERT-based model is applied to learn the text-based representation of biomarker\u2013disease relation from biomedical literature. The captured graph and text features are then integrated in a bimodal fusion network to model the hybrid entity representation. Finally, inductive matrix completion is adopted to infer the missing entries for reconstructing relation matrix, with which the unknown biomarker\u2013disease associations are predicted. Experimental results on HMDD, HMDAD and LncRNADisease data sets showed that GTGenie can obtain competitive prediction performance with other state-of-the-art methods.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability<\/jats:title><jats:p>The source code of GTGenie and the test data are available at: https:\/\/github.com\/Wolverinerine\/GTGenie.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bib\/bbac298","type":"journal-article","created":{"date-parts":[[2022,7,28]],"date-time":"2022-07-28T20:29:27Z","timestamp":1659040167000},"source":"Crossref","is-referenced-by-count":7,"title":["Prediction of biomarker\u2013disease associations based on graph attention network and text representation"],"prefix":"10.1093","volume":"23","author":[{"given":"Minghao","family":"Yang","sequence":"first","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University , Shenzhen, 518000 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhi-An","family":"Huang","sequence":"additional","affiliation":[{"name":"Center for Computer Science and Information Technology, City University of Hong Kong Dongguan Research Institute , Dongguan , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenhao","family":"Gu","sequence":"additional","affiliation":[{"name":"College of Computer Science and Software Engineering, Shenzhen University , Shenzhen, 518000 , China"},{"name":"GeneGenieDx Corp , 160 E Tasman Dr, San Jose, CA 95134"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kun","family":"Han","sequence":"additional","affiliation":[{"name":"GeneGenieDx Corp , 160 E Tasman Dr, San Jose, CA 95134"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenying","family":"Pan","sequence":"additional","affiliation":[{"name":"GeneGenieDx Corp , 160 E Tasman Dr, San Jose, CA 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