{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T05:59:08Z","timestamp":1774245548544,"version":"3.50.1"},"reference-count":49,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2023,7,18]],"date-time":"2023-07-18T00:00:00Z","timestamp":1689638400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/501100005047","name":"Natural Science Foundation of Liaoning Province","doi-asserted-by":"publisher","award":["11805091"],"award-info":[{"award-number":["11805091"]}],"id":[{"id":"10.13039\/501100005047","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005047","name":"Natural Science Foundation of Liaoning Province","doi-asserted-by":"publisher","award":["12090052"],"award-info":[{"award-number":["12090052"]}],"id":[{"id":"10.13039\/501100005047","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Foundation of Education Department of Liaoning Province","award":["LJKZ0320"],"award-info":[{"award-number":["LJKZ0320"]}]},{"name":"Foundation of Education Department of Liaoning Province","award":["LJKZ0280"],"award-info":[{"award-number":["LJKZ0280"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2023-MS-288"],"award-info":[{"award-number":["2023-MS-288"]}],"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":["2021ZD0201900"],"award-info":[{"award-number":["2021ZD0201900"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,20]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Metabolism refers to a series of orderly chemical reactions used to maintain life activities in organisms. In healthy individuals, metabolism remains within a normal range. However, specific diseases can lead to abnormalities in the levels of certain metabolites, causing them to either increase or decrease. Detecting these deviations in metabolite levels can aid in diagnosing a disease. Traditional biological experiments often rely on a lot of manpower to do repeated experiments, which is time consuming and labor intensive. To address this issue, we develop a deep learning model based on the auto-encoder and non-negative matrix factorization named as MDA-AENMF to predict the potential associations between metabolites and diseases. We integrate a variety of similarity networks and then acquire the characteristics of both metabolites and diseases through three specific modules. First, we get the disease characteristics from the five-layer auto-encoder module. Later, in the non-negative matrix factorization module, we extract both the metabolite and disease characteristics. Furthermore, the graph attention auto-encoder module helps us obtain metabolite characteristics. After obtaining the features from three modules, these characteristics are merged into a single, comprehensive feature vector for each metabolite\u2013disease pair. Finally, we send the corresponding feature vector and label to the multi-layer perceptron for training. The experiment demonstrates our area under the receiver operating characteristic curve of 0.975 and area under the precision\u2013recall curve of 0.973 in 5-fold cross-validation, which are superior to those of existing state-of-the-art predictive methods. Through case studies, most of the new associations obtained by MDA-AENMF have been verified, further highlighting the reliability of MDA-AENMF in predicting the potential relationships between metabolites and diseases.<\/jats:p>","DOI":"10.1093\/bib\/bbad259","type":"journal-article","created":{"date-parts":[[2023,7,19]],"date-time":"2023-07-19T11:27:57Z","timestamp":1689766077000},"source":"Crossref","is-referenced-by-count":126,"title":["Predicting metabolite\u2013disease associations based on auto-encoder and non-negative matrix factorization"],"prefix":"10.1093","volume":"24","author":[{"given":"Hongyan","family":"Gao","sequence":"first","affiliation":[{"name":"University of Science and Technology Liaoning School of Computer Science and Software Engineering, , Anshan, 114051 , China"}]},{"given":"Jianqiang","family":"Sun","sequence":"additional","affiliation":[{"name":"Linyi University School of Automation and Electrical Engineering, , Linyi, 276000 , China"}]},{"given":"Yukun","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Science and Technology Liaoning School of Electronic and Information Engineering, , Anshan, 114051 , China"}]},{"given":"Yuer","family":"Lu","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences Wenzhou Institute and Wenzhou Key Laboratory of Biophysics, , Wenzhou, 325001 , China"}]},{"given":"Liyu","family":"Liu","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences Wenzhou Institute and Wenzhou Key Laboratory of Biophysics, , Wenzhou, 325001 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9713-1864","authenticated-orcid":false,"given":"Qi","family":"Zhao","sequence":"additional","affiliation":[{"name":"University of Science and Technology Liaoning School of Computer Science and Software Engineering, , Anshan, 114051 , China"},{"name":"University of Chinese Academy of Sciences Wenzhou Institute and Wenzhou Key Laboratory of Biophysics, , Wenzhou, 325001 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8712-0544","authenticated-orcid":false,"given":"Jianwei","family":"Shuai","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences Wenzhou Institute and Wenzhou Key Laboratory of Biophysics, , Wenzhou, 325001 , China"}]}],"member":"286","published-online":{"date-parts":[[2023,7,18]]},"reference":[{"key":"2023092216480901000_ref1","doi-asserted-by":"crossref","first-page":"1415","DOI":"10.1016\/S0140-6736(05)66378-7","article-title":"The metabolic syndrome","volume":"365","author":"Eckel","year":"2005","journal-title":"Lancet"},{"key":"2023092216480901000_ref2","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1046\/j.1467-789X.2001.00040.x","article-title":"Quality of life and obesity","volume":"2","author":"Kolotkin","year":"2001","journal-title":"Obes 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