{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T00:30:02Z","timestamp":1769992202519,"version":"3.49.0"},"reference-count":23,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2021,8,27]],"date-time":"2021-08-27T00:00:00Z","timestamp":1630022400000},"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":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["11701296"],"award-info":[{"award-number":["11701296"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100006606","name":"Natural Science Foundation of Tianjin","doi-asserted-by":"publisher","award":["18JCQNJC09600"],"award-info":[{"award-number":["18JCQNJC09600"]}],"id":[{"id":"10.13039\/501100006606","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Laboratory for Medical Data Analysis and Statistical Research of Tianjin"},{"name":"Natural Science Foundation Project of Hebei","award":["F2019402078"],"award-info":[{"award-number":["F2019402078"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,12,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>The solvent accessible surface is an essential structural property measure related to the protein structure and protein function. Relative solvent accessible area (RSA) is a standard measure to describe the degree of residue exposure in the protein surface or inside of protein. However, this computation will fail when the residues information is missing.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>In this article, we proposed a novel method for estimation RSA using the C\u03b1 atom distance matrix with the deep learning method (EAGERER). The new method, EAGERER, achieves Pearson correlation coefficients of 0.921\u20130.928 on two independent test datasets. We empirically demonstrate that EAGERER can yield better Pearson correlation coefficients than existing RSA estimators, such as coordination number, half sphere exposure and SphereCon. To the best of our knowledge, EAGERER represents the first method to estimate the solvent accessible area using limited information with a deep learning model. It could be useful to the protein structure and protein function prediction.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availabilityand implementation<\/jats:title>\n                  <jats:p>The method is free available at https:\/\/github.com\/cliffgao\/EAGERER.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab616","type":"journal-article","created":{"date-parts":[[2021,8,27]],"date-time":"2021-08-27T22:43:30Z","timestamp":1630104210000},"page":"94-98","source":"Crossref","is-referenced-by-count":7,"title":["Precise estimation of residue relative solvent accessible area from C\u03b1 atom distance matrix using a deep learning method"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9943-4786","authenticated-orcid":false,"given":"Jianzhao","family":"Gao","sequence":"first","affiliation":[{"name":"School of Mathematical Sciences and LPMC, Nankai University , Tianjin 300071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuangjia","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Sun Yat-Sen University , Guangzhou 510006, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengting","family":"Yao","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences and LPMC, Nankai University , Tianjin 300071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peikun","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences and LPMC, Nankai University , Tianjin 300071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2021,8,27]]},"reference":[{"key":"2023020108400180500_btab616-B1","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1006\/jmbi.2001.4870","article-title":"Automated structure-based prediction of functional sites in proteins: applications to assessing the validity of inheriting protein function from homology in genome annotation and to protein docking","volume":"311","author":"Aloy","year":"2001","journal-title":"J. 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