{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T17:18:31Z","timestamp":1779211111470,"version":"3.51.4"},"reference-count":33,"publisher":"Oxford University Press (OUP)","issue":"6","license":[{"start":{"date-parts":[[2018,8,29]],"date-time":"2018-08-29T00:00:00Z","timestamp":1535500800000},"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":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"NSFC","doi-asserted-by":"publisher","award":["11501306"],"award-info":[{"award-number":["11501306"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"NSFC","doi-asserted-by":"publisher","award":["11501407"],"award-info":[{"award-number":["11501407"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"NSFC","doi-asserted-by":"publisher","award":["11871290"],"award-info":[{"award-number":["11871290"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"NSFC","doi-asserted-by":"publisher","award":["61873185"],"award-info":[{"award-number":["61873185"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004806","name":"Fok Ying-Tong Education Foundation","doi-asserted-by":"crossref","award":["161003"],"award-info":[{"award-number":["161003"]}],"id":[{"id":"10.13039\/501100004806","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Thousand Youth Talents Plan of China"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,3,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>The interactions between protein and nucleic acids play a key role in various biological processes. Accurate recognition of the residues that bind nucleic acids can facilitate the study of uncharacterized protein\u2013nucleic acids interactions. The accuracy of existing nucleic acids-binding residues prediction methods is relatively low.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In this work, we introduce NucBind, a novel method for the prediction of nucleic acids-binding residues. NucBind combines the predictions from a support vector machine-based ab-initio method SVMnuc and a template-based method COACH-D. SVMnuc was trained with features from three complementary sequence profiles. COACH-D predicts the binding residues based on homologous templates identified from a nucleic acids-binding library. The proposed methods were assessed and compared with other peering methods on three benchmark datasets. Experimental results show that NucBind consistently outperforms other state-of-the-art methods. Though with higher accuracy, similar to many other ab-initio methods, cross prediction between DNA and RNA-binding residues was also observed in SVMnuc and NucBind. We attribute the success of NucBind to two folds. The first is the utilization of improved features extracted from three complementary sequence profiles in SVMnuc. The second is the combination of two complementary methods: the ab-initio method SVMnuc and the template-based method COACH-D.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>http:\/\/yanglab.nankai.edu.cn\/NucBind<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/bty756","type":"journal-article","created":{"date-parts":[[2018,8,29]],"date-time":"2018-08-29T19:37:49Z","timestamp":1535571469000},"page":"930-936","source":"Crossref","is-referenced-by-count":94,"title":["Improving the prediction of protein\u2013nucleic acids binding residues via multiple sequence profiles and the consensus of complementary methods"],"prefix":"10.1093","volume":"35","author":[{"given":"Hong","family":"Su","sequence":"first","affiliation":[{"name":"School of Mathematical Sciences, Nankai University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengchen","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences, Nankai University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saisai","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences, Nankai University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenling","family":"Peng","sequence":"additional","affiliation":[{"name":"Center for Applied Mathematics, Tianjin University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2912-7737","authenticated-orcid":false,"given":"Jianyi","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences, Nankai University, Tianjin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2018,8,29]]},"reference":[{"key":"2023013107264088400_bty756-B1","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1186\/1471-2105-6-33","article-title":"PSSM-based prediction of DNA binding sites in proteins","volume":"6","author":"Ahmad","year":"2005","journal-title":"BMC Bioinformatics"},{"key":"2023013107264088400_bty756-B2","doi-asserted-by":"crossref","first-page":"3389","DOI":"10.1093\/nar\/25.17.3389","article-title":"Gapped BLAST and PSI-BLAST: a new generation of protein database search programs","volume":"25","author":"Altschul","year":"1997","journal-title":"Nucleic Acids Res"},{"key":"2023013107264088400_bty756-B3","doi-asserted-by":"crossref","first-page":"W249","DOI":"10.1093\/nar\/gks481","article-title":"DR_bind: a web server for predicting DNA-binding residues from the protein structure based on electrostatics, evolution and geometry","volume":"40","author":"Chen","year":"2012","journal-title":"Nucleic Acids Res"},{"key":"2023013107264088400_bty756-B4","doi-asserted-by":"crossref","first-page":"W396","DOI":"10.1093\/nar\/gkp449","article-title":"ProteDNA: a sequence-based predictor of sequence-specific DNA-binding residues in transcription factors","volume":"37","author":"Chu","year":"2009","journal-title":"Nucleic Acids Res"},{"key":"2023013107264088400_bty756-B5","first-page":"W380","article-title":"mTM-align: a server for fast protein structure database search and multiple protein structure alignment","volume":"46","author":"Dong","year":"2018","journal-title":"Nucleic Acids Res"},{"key":"2023013107264088400_bty756-B6","doi-asserted-by":"crossref","first-page":"634","DOI":"10.1093\/bioinformatics\/btl672","article-title":"DP-Bind: a web server for sequence-based prediction of DNA-binding residues in DNA-binding proteins","volume":"23","author":"Hwang","year":"2007","journal-title":"Bioinformatics"},{"key":"2023013107264088400_bty756-B7","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1006\/jmbi.1999.3091","article-title":"Protein secondary structure prediction based on position-specific scoring matrices","volume":"292","author":"Jones","year":"1999","journal-title":"J. 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