{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T16:56:21Z","timestamp":1762102581988,"version":"3.37.3"},"reference-count":83,"publisher":"Oxford University Press (OUP)","issue":"24","license":[{"start":{"date-parts":[[2020,12,26]],"date-time":"2020-12-26T00:00:00Z","timestamp":1608940800000},"content-version":"vor","delay-in-days":11,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62001090","91935302","61922020","61822108","61771331"],"award-info":[{"award-number":["62001090","91935302","61922020","61822108","61771331"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2020M673184"],"award-info":[{"award-number":["2020M673184"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,4,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>The Golgi apparatus has a key functional role in protein biosynthesis within the eukaryotic cell with malfunction resulting in various neurodegenerative diseases. For a better understanding of the Golgi apparatus, it is essential to identification of sub-Golgi protein localization. Although some machine learning methods have been used to identify sub-Golgi localization proteins by sequence representation fusion, more accurate sub-Golgi protein identification is still challenging by existing methodology.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>we developed a protein sub-Golgi localization identification protocol using deep representation learning features with 107 dimensions. By this protocol, we demonstrated that instead of multi-type protein sequence feature representation fusion as in previous state-of-the-art sub-Golgi-protein localization classifiers, it is sufficient to exploit only one type of feature representation for more accurately identification of sub-Golgi proteins. Compared with independent testing results for benchmark datasets, our protocol is able to perform generally, reliably and robustly for sub-Golgi protein localization prediction.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availabilityand implementation<\/jats:title>\n                  <jats:p>A use-friendly webserver is freely accessible at http:\/\/isGP-DRLF.aibiochem.net and the prediction code is accessible at https:\/\/github.com\/zhibinlv\/isGP-DRLF.<\/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\/btaa1074","type":"journal-article","created":{"date-parts":[[2020,12,14]],"date-time":"2020-12-14T20:22:47Z","timestamp":1607977367000},"page":"5600-5609","source":"Crossref","is-referenced-by-count":55,"title":["Identification of sub-Golgi protein localization by use of deep representation learning features"],"prefix":"10.1093","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5390-7616","authenticated-orcid":false,"given":"Zhibin","family":"Lv","sequence":"first","affiliation":[{"name":"Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China , Chengdu, China"}]},{"given":"Pingping","family":"Wang","sequence":"additional","affiliation":[{"name":"Center for Bioinformatics, School of Life Science and Technology, Harbin Institute of Technology , Harbin 150000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6406-1142","authenticated-orcid":false,"given":"Quan","family":"Zou","sequence":"additional","affiliation":[{"name":"Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China , Chengdu, China"},{"name":"Center for Informational Biology, University of Electronic Science and Technology of China , Chengdu, China"},{"name":"Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China , Quzhou, Zhejiang, China"}]},{"given":"Qinghua","family":"Jiang","sequence":"additional","affiliation":[{"name":"Center for Bioinformatics, School of Life Science and Technology, Harbin Institute of Technology , Harbin 150000, China"}]}],"member":"286","published-online":{"date-parts":[[2020,12,26]]},"reference":[{"key":"2023062408114287300_btaa1074-B1","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.jtbi.2018.12.017","article-title":"MFSC: multi-voting based feature selection for classification of Golgi proteins by adopting the general form of Chou's PseAAC components","volume":"463","author":"Ahmad","year":"2019","journal-title":"J. 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