{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T08:13:58Z","timestamp":1768983238881,"version":"3.49.0"},"reference-count":58,"publisher":"Oxford University Press (OUP)","issue":"6","license":[{"start":{"date-parts":[[2022,9,27]],"date-time":"2022-09-27T00:00:00Z","timestamp":1664236800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["NSFC 62172296"],"award-info":[{"award-number":["NSFC 62172296"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2021YFC2100700"],"award-info":[{"award-number":["2021YFC2100700"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,11,19]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Metabolomics has developed rapidly in recent years, and metabolism-related databases are also gradually constructed. Nowadays, more and more studies are being carried out on diverse microbes, metabolites and diseases. However, the logics of various associations among microbes, metabolites and diseases are limited understanding in the biomedicine of gut microbial system. The collection and analysis of relevant microbial bioinformation play an important role in the revelation of microbe\u2013metabolite\u2013disease associations. Therefore, the dataset that integrates multiple relationships and the method based on complex heterogeneous graphs need to be developed.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>In this study, we integrated some databases and extracted a variety of associations data among microbes, metabolites and diseases. After obtaining the three interconnected bilateral association data (microbe\u2013metabolite, metabolite\u2013disease and disease\u2013microbe), we considered building a heterogeneous graph to describe the association data. In our model, microbes were used as a bridge between diseases and metabolites. In order to fuse the information of disease\u2013microbe\u2013metabolite graph, we used the bipartite graph attention network on the disease\u2013microbe and metabolite\u2013microbe bipartite graph. The experimental results show that our model has good performance in the prediction of various disease\u2013metabolite associations. Through the case study of type 2 diabetes mellitus, Parkinson\u2019s disease, inflammatory bowel disease and liver cirrhosis, it is noted that our proposed methodology are valuable for the mining of other associations and the prediction of biomarkers for different human diseases.<\/jats:p>\n                  <jats:p>Availability and implementation: https:\/\/github.com\/Selenefreeze\/DiMiMe.git<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bib\/bbac423","type":"journal-article","created":{"date-parts":[[2022,9,28]],"date-time":"2022-09-28T06:38:50Z","timestamp":1664347130000},"source":"Crossref","is-referenced-by-count":19,"title":["Microbe-bridged disease-metabolite associations identification by heterogeneous graph fusion"],"prefix":"10.1093","volume":"23","author":[{"given":"Jitong","family":"Feng","sequence":"first","affiliation":[{"name":"College of Intelligence and Computing, Tianjin University , Tianjin, China"}]},{"given":"Shengbo","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Chemical Engineering and Technology, Tianjin University , Tianjin, China"},{"name":"Zhejiang Shaoxing Research Institute of Tianjin University , Shaoxing, China"}]},{"given":"Hongpeng","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Computational Science and Engineering, University of South Carolina , Columbia, U.S"}]},{"given":"Chengwei","family":"Ai","sequence":"additional","affiliation":[{"name":"College of Intelligence and Computing, Tianjin University , Tianjin, China"}]},{"given":"Jianjun","family":"Qiao","sequence":"additional","affiliation":[{"name":"School of Chemical Engineering and Technology, Tianjin University , Tianjin, China"},{"name":"Zhejiang Shaoxing Research Institute of Tianjin University , Shaoxing, China"}]},{"given":"Junhai","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Intelligence and Computing, Tianjin University , Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8346-0798","authenticated-orcid":false,"given":"Fei","family":"Guo","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University , Changsha, China"}]}],"member":"286","published-online":{"date-parts":[[2022,9,27]]},"reference":[{"issue":"7","key":"2022112111124851000_ref1","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1038\/nrd.2016.32","article-title":"Emerging applications of metabolomics in drug discovery and precision medicine","volume":"15","author":"Wishart","year":"2016","journal-title":"Nat Rev Drug Discov"},{"issue":"1","key":"2022112111124851000_ref2","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1093\/bib\/bbx103","article-title":"MetSigDis: a manually curated resource for the metabolic signatures of diseases","volume":"20","author":"Cheng","year":"2019","journal-title":"Brief 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