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Journal Abstract Search

195 related items for PubMed ID: 18432623

  • 1. Using support vector machine to predict beta- and gamma-turns in proteins.
    Hu X, Li Q.
    J Comput Chem; 2008 Sep; 29(12):1867-75. PubMed ID: 18432623
    [Abstract] [Full Text] [Related]

  • 2. Prediction of pi-turns in proteins using PSI-BLAST profiles and secondary structure information.
    Wang Y, Xue ZD, Shi XH, Xu J.
    Biochem Biophys Res Commun; 2006 Sep 01; 347(3):574-80. PubMed ID: 16844090
    [Abstract] [Full Text] [Related]

  • 3. A neural network method for prediction of beta-turn types in proteins using evolutionary information.
    Kaur H, Raghava GP.
    Bioinformatics; 2004 Nov 01; 20(16):2751-8. PubMed ID: 15145798
    [Abstract] [Full Text] [Related]

  • 4. A neural-network based method for prediction of gamma-turns in proteins from multiple sequence alignment.
    Kaur H, Raghava GP.
    Protein Sci; 2003 May 01; 12(5):923-9. PubMed ID: 12717015
    [Abstract] [Full Text] [Related]

  • 5. gamma-Turn types prediction in proteins using the support vector machines.
    Jahandideh S, Sarvestani AS, Abdolmaleki P, Jahandideh M, Barfeie M.
    J Theor Biol; 2007 Dec 21; 249(4):785-90. PubMed ID: 17936305
    [Abstract] [Full Text] [Related]

  • 6. Prediction of β-turn types in protein by using composite vector.
    Shi X, Hu X, Li S, Liu X.
    J Theor Biol; 2011 Oct 07; 286(1):24-30. PubMed ID: 21781975
    [Abstract] [Full Text] [Related]

  • 7. Better prediction of the location of alpha-turns in proteins with support vector machine.
    Wang Y, Xue Z, Xu J.
    Proteins; 2006 Oct 01; 65(1):49-54. PubMed ID: 16894602
    [Abstract] [Full Text] [Related]

  • 8. Prediction and analysis of beta-turns in proteins by support vector machine.
    Pham TH, Satou K, Ho TB.
    Genome Inform; 2003 Oct 01; 14():196-205. PubMed ID: 15706534
    [Abstract] [Full Text] [Related]

  • 9. Improved method for predicting beta-turn using support vector machine.
    Zhang Q, Yoon S, Welsh WJ.
    Bioinformatics; 2005 May 15; 21(10):2370-4. PubMed ID: 15797917
    [Abstract] [Full Text] [Related]

  • 10. Using predicted shape string to enhance the accuracy of γ-turn prediction.
    Zhu Y, Li T, Li D, Zhang Y, Xiong W, Sun J, Tang Z, Chen G.
    Amino Acids; 2012 May 15; 42(5):1749-55. PubMed ID: 21424809
    [Abstract] [Full Text] [Related]

  • 11. Prediction of turn types in protein structure by machine-learning classifiers.
    Meissner M, Koch O, Klebe G, Schneider G.
    Proteins; 2009 Feb 01; 74(2):344-52. PubMed ID: 18618702
    [Abstract] [Full Text] [Related]

  • 12. Support vector machines for the classification and prediction of beta-turn types.
    Cai YD, Liu XJ, Xu XB, Chou KC.
    J Pept Sci; 2002 Jul 01; 8(7):297-301. PubMed ID: 12148778
    [Abstract] [Full Text] [Related]

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  • 14. Prediction of transmembrane regions of beta-barrel proteins using ANN- and SVM-based methods.
    Natt NK, Kaur H, Raghava GP.
    Proteins; 2004 Jul 01; 56(1):11-8. PubMed ID: 15162482
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  • 16. Using support vector machines for prediction of protein structural classes based on discrete wavelet transform.
    Qiu JD, Luo SH, Huang JH, Liang RP.
    J Comput Chem; 2009 Jun 01; 30(8):1344-50. PubMed ID: 19009604
    [Abstract] [Full Text] [Related]

  • 17. Recognition of beta-hairpin motifs in proteins by using the composite vector.
    Hu XZ, Li QZ, Wang CL.
    Amino Acids; 2010 Mar 01; 38(3):915-21. PubMed ID: 19418016
    [Abstract] [Full Text] [Related]

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