{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T15:21:45Z","timestamp":1759332105324},"reference-count":16,"publisher":"Oxford University Press (OUP)","issue":"19","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":2232,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/2.0\/uk\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: We present a novel Golgi-prediction server, GolgiP, for computational prediction of both membrane- and non-membrane-associated Golgi-resident proteins in plants. We have employed a support vector machine-based classification method for the prediction of such Golgi proteins, based on three types of information, dipeptide composition, transmembrane domain(s) (TMDs) and functional domain(s) of a protein, where the functional domain information is generated through searching against the Conserved Domains Database, and the TMD information includes the number of TMDs, the length of TMD and the number of TMDs at the N-terminus of a protein. Using GolgiP, we have made genome-scale predictions of Golgi-resident proteins in 18 plant genomes, and have made the preliminary analysis of the predicted data.<\/jats:p>\n               <jats:p>Availability: The GolgiP web service is publically available at http:\/\/csbl1.bmb.uga.edu\/GolgiP\/<\/jats:p>\n               <jats:p>Contact: \u00a0xyn@csbl.bmb.uga.edu<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq446","type":"journal-article","created":{"date-parts":[[2010,8,24]],"date-time":"2010-08-24T02:45:35Z","timestamp":1282617935000},"page":"2464-2465","source":"Crossref","is-referenced-by-count":11,"title":["GolgiP: prediction of Golgi-resident proteins in plants"],"prefix":"10.1093","volume":"26","author":[{"given":"Wen-Chi","family":"Chou","sequence":"first","affiliation":[{"name":"1 Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology, and Institute of Bioinformatics, University of Georgia, 2BioEnergy Science Center, USA and 3College of Computer Science and Technology, Jilin University, Changchun, Jilin, China"},{"name":"1 Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology, and Institute of Bioinformatics, University of Georgia, 2BioEnergy Science Center, USA and 3College of Computer Science and Technology, Jilin University, Changchun, Jilin, China"}]},{"given":"Yanbin","family":"Yin","sequence":"additional","affiliation":[{"name":"1 Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology, and Institute of Bioinformatics, University of Georgia, 2BioEnergy Science Center, USA and 3College of Computer Science and Technology, Jilin University, Changchun, Jilin, China"},{"name":"1 Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology, and Institute of Bioinformatics, University of Georgia, 2BioEnergy Science Center, USA and 3College of Computer Science and Technology, Jilin University, Changchun, Jilin, China"}]},{"given":"Ying","family":"Xu","sequence":"additional","affiliation":[{"name":"1 Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology, and Institute of Bioinformatics, University of Georgia, 2BioEnergy Science Center, USA and 3College of Computer Science and Technology, Jilin University, Changchun, Jilin, China"},{"name":"1 Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology, and Institute of Bioinformatics, University of Georgia, 2BioEnergy Science Center, USA and 3College of Computer Science and Technology, Jilin University, Changchun, Jilin, China"},{"name":"1 Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology, and Institute of Bioinformatics, University of Georgia, 2BioEnergy Science Center, USA and 3College of Computer Science and Technology, Jilin University, Changchun, Jilin, China"}]}],"member":"286","published-online":{"date-parts":[[2010,8,23]]},"reference":[{"key":"2023012508173519400_B1","doi-asserted-by":"crossref","first-page":"D115","DOI":"10.1093\/nar\/gkh131","article-title":"UniProt: the Universal Protein knowledgebase","volume":"32","author":"Apweiler","year":"2004","journal-title":"Nucleic Acids Res."},{"key":"2023012508173519400_B2","first-page":"1889","article-title":"Working set selection using second order information for training SVM","volume":"6","author":"Fan","year":"2005","journal-title":"J. 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