TY - GEN
T1 - Protein folding classification by committee SVM array
AU - Takata, Mika
AU - Matsuyama, Yasuo
PY - 2009
Y1 - 2009
N2 - Protein folding classification is a meaningful step to improve analysis of the whole structures. We have designed committee Support Vector Machines (committee SVMs) and their array (committee SVM array) for the prediction of the folding classes. Learning and test data are amino acid sequences drawn from SCOP (Structure Classification Of Protein database). The classification category is compatible with the SCOP. SVMs and committee SVMs are designed in an one-versus-others style both for chemical data and sliding window patterns (spectrum kernels). This generates the committee SVM array. Classification performances are measured in view of the Receiver Operating Characteristic curves (ROC). Superiority of the committee SVM array to existing prediction methods is obtained through extensive experiments to compute the ROCs.
AB - Protein folding classification is a meaningful step to improve analysis of the whole structures. We have designed committee Support Vector Machines (committee SVMs) and their array (committee SVM array) for the prediction of the folding classes. Learning and test data are amino acid sequences drawn from SCOP (Structure Classification Of Protein database). The classification category is compatible with the SCOP. SVMs and committee SVMs are designed in an one-versus-others style both for chemical data and sliding window patterns (spectrum kernels). This generates the committee SVM array. Classification performances are measured in view of the Receiver Operating Characteristic curves (ROC). Superiority of the committee SVM array to existing prediction methods is obtained through extensive experiments to compute the ROCs.
UR - http://www.scopus.com/inward/record.url?scp=70349141356&partnerID=8YFLogxK
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U2 - 10.1007/978-3-642-03040-6_45
DO - 10.1007/978-3-642-03040-6_45
M3 - Conference contribution
AN - SCOPUS:70349141356
SN - 3642030394
SN - 9783642030390
VL - 5507 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 369
EP - 377
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 15th International Conference on Neuro-Information Processing, ICONIP 2008
Y2 - 25 November 2008 through 28 November 2008
ER -