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Volumn , Issue , 2008, Pages

Fast protein homology and fold detection with sparse spatial sample Kernels

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARKING; MACHINE LEARNING; PROTEINS; SUPERVISED LEARNING;

EID: 77957967988     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/icpr.2008.4761450     Document Type: Conference Paper
Times cited : (11)

References (17)
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  • 7
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    • Use of receiver operating characteristic (roc) analysis to evaluate sequence matching
    • M. Gribskov and N. L. Robinson. Use of receiver operating characteristic (roc) analysis to evaluate sequence matching. Computers & Chemistry, 20(1):25-33, 1996.
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  • 8
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    • T. Jaakkola, M. Diekhans, and D. Haussler. A discriminative framework for detecting remote protein homologies. In J. Comp. Biol., volume 7, pages 95-114, 2000.
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    • Jaakkola, T.1    Diekhans, M.2    Haussler, D.3
  • 9
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    • Profile-based string kernels for remote homology detection and motif extraction
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    • R. Kuang, E. Ie, K. Wang, K. Wang, M. Siddiqi, Y. Freund, and C. Leslie. Profile-based string kernels for remote homology detection and motif extraction. In CSB, pages 152-160, August 2004.
    • (2004) CSB , pp. 152-160
    • Kuang, R.1    Ie, E.2    Wang, K.3    Wang, K.4    Siddiqi, M.5    Freund, Y.6    Leslie, C.7
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.