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Volumn 23, Issue 20, 2007, Pages 2795-2796

TMpro web server and web service: Transmembrane helix prediction through amino acid property analysis

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID; MEMBRANE PROTEIN;

EID: 35748979116     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btm398     Document Type: Article
Times cited : (10)

References (4)
  • 1
    • 84872004750 scopus 로고    scopus 로고
    • Transmembrane helix prediction using amino acid property features and latent semantic analysis
    • Hong Kong SAR
    • Ganapathiraju,M. et al. (2007) Transmembrane helix prediction using amino acid property features and latent semantic analysis. InCoB2007, Hong Kong SAR. http://srs1.bic.nus.edu.sg/ocs/ viewabstract.php?id=46
    • (2007) InCoB2007
    • Ganapathiraju, M.1
  • 2
    • 0035910270 scopus 로고    scopus 로고
    • Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes
    • Krogh,A. et al. (2001) Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes. J. Mol Biol., 305, 567-580.
    • (2001) J. Mol Biol , vol.305 , pp. 567-580
    • Krogh, A.1
  • 3
    • 0020475449 scopus 로고
    • A simple method for displaying the hydropathic character of a protein
    • Kyte,J. and Doolittle,R.F. (1982) A simple method for displaying the hydropathic character of a protein. J. Mol. Biol., 157, 105-132.
    • (1982) J. Mol. Biol , vol.157 , pp. 105-132
    • Kyte, J.1    Doolittle, R.F.2
  • 4
    • 3042579686 scopus 로고    scopus 로고
    • Best alpha-helical transmembrane protein topology predictions are achieved using hidden Markov models and evolutionary information
    • Viklund,H. and Elofsson,A. (2004) Best alpha-helical transmembrane protein topology predictions are achieved using hidden Markov models and evolutionary information. Protein Sci., 13, 1908-1917.
    • (2004) Protein Sci , vol.13 , pp. 1908-1917
    • Viklund, H.1    Elofsson, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.