메뉴 건너뛰기




Volumn 17, Issue 8, 2001, Pages 721-728

Support vector machine approach for protein subcellular localization prediction

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID;

EID: 0034843744     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/17.8.721     Document Type: Article
Times cited : (775)

References (33)
  • 6
    • 0034714135 scopus 로고    scopus 로고
    • A Bayesian system integrating expression data with sequence patterns for localizing proteins: Comprehensive application to the yeast genome
    • (2000) J. Mol. Biol. , vol.301 , pp. 1059-1075
    • Drawid, A.1    Gerstein, M.2
  • 13
    • 0035957531 scopus 로고    scopus 로고
    • A novel method of protein secondary structure prediction with high segment overlap measure: Support vector machine approach
    • in press.
    • (2001) J. Mol. Biol.
    • Hua, S.J.1    Sun, Z.R.2
  • 21
    • 0027105007 scopus 로고
    • A knowledge base for predicting protein localization sites in eukaryotic cells
    • (1992) Genomics , vol.14 , pp. 897-911
    • Nakai, K.1    Kanehisa, M.2
  • 22
  • 33
    • 0032938624 scopus 로고    scopus 로고
    • Prediction of protein subcellular locations using Markov chain models
    • (1999) FEBS Lett. , vol.451 , pp. 23-26
    • Yuan, Z.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.