{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T01:08:35Z","timestamp":1773277715878,"version":"3.50.1"},"reference-count":28,"publisher":"Oxford University Press (OUP)","issue":"9","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2007,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: This work aims to develop computational methods to annotate protein structures in an automated fashion. We employ a support vector machine (SVM) classifier to map from a given class of structures to their corresponding structural (SCOP) or functional (Gene Ontology) annotation. In particular, we build upon recent work describing various kernels for protein structures, where a kernel is a similarity function that the classifier uses to compare pairs of structures.<\/jats:p><jats:p>Results: We describe a kernel that is derived in a straightforward fashion from an existing structural alignment program, MAMMOTH. We find in our benchmark experiments that this kernel significantly out-performs a variety of other kernels, including several previously described kernels. Furthermore, in both benchmarks, classifying structures using MAMMOTH alone does not work as well as using an SVM with the MAMMOTH kernel.<\/jats:p><jats:p>Availability: \u00a0http:\/\/noble.gs.washington.edu\/proj\/3dkernel<\/jats:p><jats:p>Contact: \u00a0noble@gs.washington.edu<\/jats:p>","DOI":"10.1093\/bioinformatics\/btl642","type":"journal-article","created":{"date-parts":[[2007,1,19]],"date-time":"2007-01-19T01:13:12Z","timestamp":1169169192000},"page":"1090-1098","source":"Crossref","is-referenced-by-count":33,"title":["A structural alignment kernel for protein structures"],"prefix":"10.1093","volume":"23","author":[{"given":"Jian","family":"Qiu","sequence":"first","affiliation":[{"name":"1 Department of Genome Sciences, 2Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA, 3Center for Computational Biology, Ecole des Mines de Paris, Fontainebleau, France and 4Department of Computer Science, Colorado State University, Ft. Collins, CO, USA"}]},{"given":"Martial","family":"Hue","sequence":"additional","affiliation":[{"name":"1 Department of Genome Sciences, 2Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA, 3Center for Computational Biology, Ecole des Mines de Paris, Fontainebleau, France and 4Department of Computer Science, Colorado State University, Ft. Collins, CO, USA"}]},{"given":"Asa","family":"Ben-Hur","sequence":"additional","affiliation":[{"name":"1 Department of Genome Sciences, 2Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA, 3Center for Computational Biology, Ecole des Mines de Paris, Fontainebleau, France and 4Department of Computer Science, Colorado State University, Ft. Collins, CO, USA"}]},{"given":"Jean-Philippe","family":"Vert","sequence":"additional","affiliation":[{"name":"1 Department of Genome Sciences, 2Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA, 3Center for Computational Biology, Ecole des Mines de Paris, Fontainebleau, France and 4Department of Computer Science, Colorado State University, Ft. Collins, CO, USA"}]},{"given":"William Stafford","family":"Noble","sequence":"additional","affiliation":[{"name":"1 Department of Genome Sciences, 2Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA, 3Center for Computational Biology, Ecole des Mines de Paris, Fontainebleau, France and 4Department of Computer Science, Colorado State University, Ft. Collins, CO, USA"},{"name":"1 Department of Genome Sciences, 2Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA, 3Center for Computational Biology, Ecole des Mines de Paris, Fontainebleau, France and 4Department of Computer Science, Colorado State University, Ft. Collins, CO, USA"}]}],"member":"286","published-online":{"date-parts":[[2007,1,18]]},"reference":[{"key":"2023041209111916300_","article-title":"Computing regularization paths for learning multiple kernels","volume-title":"Advances in Neural Information Processing Systems","author":"Bach","year":"2004"},{"key":"2023041209111916300_","doi-asserted-by":"crossref","first-page":"i47","DOI":"10.1093\/bioinformatics\/bti1007","article-title":"Protein function prediction via graph kernels","volume":"21","author":"Borgwardt","year":"2005","journal-title":"Bioinformatics"},{"key":"2023041209111916300_","first-page":"144","article-title":"A training algorithm for optimal margin classifiers","volume-title":"5th Annual ACM Workshop on COLT","author":"Boser","year":"1992"},{"key":"2023041209111916300_","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1093\/nar\/28.1.254","article-title":"The ASTRAL compendium for sequence and structure analysis","volume":"28","author":"Brenner","year":"2000","journal-title":"Nucleic Acids Research"},{"key":"2023041209111916300_","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.jmb.2004.10.024","article-title":"Predicting enzyme class from protein structure without alignments","volume":"345","author":"Dobson","year":"2005","journal-title":"J. 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