{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T02:03:40Z","timestamp":1776132220081,"version":"3.50.1"},"reference-count":62,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2019,9,30]],"date-time":"2019-09-30T00:00:00Z","timestamp":1569801600000},"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\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["LP110200333"],"award-info":[{"award-number":["LP110200333"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["DP120104460"],"award-info":[{"award-number":["DP120104460"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Health and Medical Research Council of Australia","award":["1092262"],"award-info":[{"award-number":["1092262"]}]},{"name":"National Health and Medical Research Council of Australia","award":["490989"],"award-info":[{"award-number":["490989"]}]},{"name":"National Institute of Allergy and Infectious Diseases of the National Institutes of Health","award":["R01 AI111965"],"award-info":[{"award-number":["R01 AI111965"]}]},{"name":"Major Inter-Disciplinary Research (IDR) Grant"},{"name":"Collaborative Research Program of Institute for Chemical Research, Kyoto University","award":["2019-32"],"award-info":[{"award-number":["2019-32"]}]},{"name":"Robert J. Mattauch Endowment funds"},{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,2,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Proteases are enzymes that cleave target substrate proteins by catalyzing the hydrolysis of peptide bonds between specific amino acids. While the functional proteolysis regulated by proteases plays a central role in the \u2018life and death\u2019 cellular processes, many of the corresponding substrates and their cleavage sites were not found yet. Availability of accurate predictors of the substrates and cleavage sites would facilitate understanding of proteases\u2019 functions and physiological roles. Deep learning is a promising approach for the development of accurate predictors of substrate cleavage events.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We propose DeepCleave, the first deep learning-based predictor of protease-specific substrates and cleavage sites. DeepCleave uses protein substrate sequence data as input and employs convolutional neural networks with transfer learning to train accurate predictive models. High predictive performance of our models stems from the use of high-quality cleavage site features extracted from the substrate sequences through the deep learning process, and the application of transfer learning, multiple kernels and attention layer in the design of the deep network. Empirical tests against several related state-of-the-art methods demonstrate that DeepCleave outperforms these methods in predicting caspase and matrix metalloprotease substrate-cleavage sites.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The DeepCleave webserver and source code are freely available at http:\/\/deepcleave.erc.monash.edu\/.<\/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\/btz721","type":"journal-article","created":{"date-parts":[[2019,9,26]],"date-time":"2019-09-26T11:28:48Z","timestamp":1569497328000},"page":"1057-1065","source":"Crossref","is-referenced-by-count":115,"title":["DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites"],"prefix":"10.1093","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5216-3213","authenticated-orcid":false,"given":"Fuyi","family":"Li","sequence":"first","affiliation":[{"name":"Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University , Melbourne, VIC 3800, Australia"},{"name":"Monash Centre for Data Science, Faculty of Information Technology , Monash University, Melbourne, VIC 3800, Australia"}]},{"given":"Jinxiang","family":"Chen","sequence":"additional","affiliation":[{"name":"Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University , Melbourne, VIC 3800, Australia"},{"name":"College of Information Engineering, Northwest A&F University , Yangling 712100, China"}]},{"given":"Andr\u00e9","family":"Leier","sequence":"additional","affiliation":[{"name":"Department of Genetics , USA"},{"name":"Department of Cell, Developmental and Integrative Biology, School of Medicine , University of Alabama at Birmingham, Birmingham, AL, USA"}]},{"given":"Tatiana","family":"Marquez-Lago","sequence":"additional","affiliation":[{"name":"Department of Genetics , USA"},{"name":"Department of Cell, Developmental and Integrative Biology, School of Medicine , University of Alabama at Birmingham, Birmingham, AL, USA"}]},{"given":"Quanzhong","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Northwest A&F University , Yangling 712100, China"}]},{"given":"Yanze","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Northwest A&F University , Yangling 712100, China"}]},{"given":"Jerico","family":"Revote","sequence":"additional","affiliation":[{"name":"Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University , Melbourne, VIC 3800, Australia"}]},{"given":"A Ian","family":"Smith","sequence":"additional","affiliation":[{"name":"Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University , Melbourne, VIC 3800, Australia"}]},{"given":"Tatsuya","family":"Akutsu","sequence":"additional","affiliation":[{"name":"Bioinformatics Center, Institute for Chemical Research, Kyoto University , Kyoto 611-0011, Japan"}]},{"given":"Geoffrey I","family":"Webb","sequence":"additional","affiliation":[{"name":"Monash Centre for Data Science, Faculty of Information Technology , Monash University, Melbourne, VIC 3800, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7749-0314","authenticated-orcid":false,"given":"Lukasz","family":"Kurgan","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Virginia Commonwealth University , Richmond, VA 23284, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8031-9086","authenticated-orcid":false,"given":"Jiangning","family":"Song","sequence":"additional","affiliation":[{"name":"Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University , Melbourne, VIC 3800, Australia"},{"name":"Monash Centre for Data Science, Faculty of Information Technology , Monash University, Melbourne, VIC 3800, Australia"},{"name":"ARC Centre of Excellence in Advanced Molecular Imaging, Monash University , Melbourne, VIC 3800, Australia"}]}],"member":"286","published-online":{"date-parts":[[2019,9,30]]},"reference":[{"key":"2023013110163044900_btz721-B1","author":"Armenteros","year":"2019"},{"key":"2023013110163044900_btz721-B2","doi-asserted-by":"crossref","first-page":"912","DOI":"10.1074\/mcp.M000032-MCP201","article-title":"A statistics-based platform for quantitative N-terminome analysis and identification of protease cleavage products","volume":"9","author":"Auf Dem Keller","year":"2010","journal-title":"Mol. 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