{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,1,26]],"date-time":"2023-01-26T05:20:25Z","timestamp":1674710425215},"reference-count":20,"publisher":"Oxford University Press (OUP)","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011,1,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: The slow growth of expert-curated databases compared to experimental databases makes it necessary to build upon highly accurate automated processing pipelines to make the most of the data until curation becomes available. We address this problem in the context of protein structures and their classification into structural and functional classes, more specifically, the structural classification of proteins (SCOP). Structural alignment methods like Vorolign already provide good classification results, but effectively work in a 1-Nearest Neighbor mode. Model-based (in contrast to instance-based) approaches so far have been shown to be of limited values due to small classes arising in such classification schemes.<\/jats:p>\n               <jats:p>Results: In this article, we describe how kernels defined in terms of Vorolign scores can be used in SVM learning, and explore variants of combined instance-based and model-based learning, up to exclusively model-based learning. Our results suggest that kernels based on Vorolign scores are effective and that model-based learning can yield highly competitive classification results for the prediction of SCOP families.<\/jats:p>\n               <jats:p>Availability: The code is made available at: http:\/\/wwwkramer.in.tum.de\/research\/applications\/vorolign-kernel.<\/jats:p>\n               <jats:p>Contact: \u00a0kramer@in.tum.de<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq618","type":"journal-article","created":{"date-parts":[[2010,11,20]],"date-time":"2010-11-20T01:23:45Z","timestamp":1290216225000},"page":"204-210","source":"Crossref","is-referenced-by-count":2,"title":["Improving structure alignment-based prediction of SCOP families using Vorolign Kernels"],"prefix":"10.1093","volume":"27","author":[{"given":"Tobias","family":"Hamp","sequence":"first","affiliation":[{"name":"1 Institut f\u00fcr Informatik\/I12, Technische Universit\u00e4t M\u00fcnchen, Boltzmannstrasse 3, D-85749 Garching b. M\u00fcnchen and 2Department of Pulmonary Research, Group Genomics, Boehringer Ingelheim Pharma GmbH & Co KG, Birkendorferstrasse 67, D-88397 Biberach an der Ri\u00df, Germany"}]},{"given":"Fabian","family":"Birzele","sequence":"additional","affiliation":[{"name":"1 Institut f\u00fcr Informatik\/I12, Technische Universit\u00e4t M\u00fcnchen, Boltzmannstrasse 3, D-85749 Garching b. M\u00fcnchen and 2Department of Pulmonary Research, Group Genomics, Boehringer Ingelheim Pharma GmbH & Co KG, Birkendorferstrasse 67, D-88397 Biberach an der Ri\u00df, Germany"}]},{"given":"Fabian","family":"Buchwald","sequence":"additional","affiliation":[{"name":"1 Institut f\u00fcr Informatik\/I12, Technische Universit\u00e4t M\u00fcnchen, Boltzmannstrasse 3, D-85749 Garching b. M\u00fcnchen and 2Department of Pulmonary Research, Group Genomics, Boehringer Ingelheim Pharma GmbH & Co KG, Birkendorferstrasse 67, D-88397 Biberach an der Ri\u00df, Germany"}]},{"given":"Stefan","family":"Kramer","sequence":"additional","affiliation":[{"name":"1 Institut f\u00fcr Informatik\/I12, Technische Universit\u00e4t M\u00fcnchen, Boltzmannstrasse 3, D-85749 Garching b. M\u00fcnchen and 2Department of Pulmonary Research, Group Genomics, Boehringer Ingelheim Pharma GmbH & Co KG, Birkendorferstrasse 67, D-88397 Biberach an der Ri\u00df, Germany"}]}],"member":"286","published-online":{"date-parts":[[2010,11,18]]},"reference":[{"key":"2023012512171073100_B1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/nar\/gkm993","article-title":"Data growth and its impact on the SCOP database: new developments","volume":"36","author":"Andreeva","year":"2007","journal-title":"Nucleic Acids Res."},{"key":"2023012512171073100_B2","doi-asserted-by":"crossref","first-page":"e205","DOI":"10.1093\/bioinformatics\/btl294","article-title":"Vorolign\u2013fast structural alignment using Voronoi contacts","volume":"23","author":"Birzele","year":"2007","journal-title":"Bioinformatics"},{"key":"2023012512171073100_B3","doi-asserted-by":"crossref","first-page":"398","DOI":"10.1093\/nar\/gkm834","article-title":"AutoPSI: a database for automatic structural classification of protein sequences and structures","volume":"36","author":"Birzele","year":"2008","journal-title":"Nucleic Acids Res."},{"key":"2023012512171073100_B4","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1186\/1471-2105-5-197","article-title":"SCOPmap: automated assignment of protein structures to evolutionary superfamilies","volume":"5","author":"Cheek","year":"2004","journal-title":"BMC Bioinformatics"},{"key":"2023012512171073100_B5","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1145\/1553374.1553393","article-title":"Learning Kernels from indefinite similarities","volume-title":"ICML '09: Proceedings of the 26th Annual International Conference on Machine Learning","author":"Chen","year":"2009"},{"key":"2023012512171073100_B6","first-page":"747","article-title":"Similarity-based classification: concepts and algorithms","volume":"10","author":"Chen","year":"2009","journal-title":"J. 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