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Journal Abstract Search

259 related items for PubMed ID: 16844090

  • 1. 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]

  • 2. 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]

  • 3. Prediction of alpha-turns in proteins using PSI-BLAST profiles and secondary structure information.
    Kaur H, Raghava GP.
    Proteins; 2004 Apr 01; 55(1):83-90. PubMed ID: 14997542
    [Abstract] [Full Text] [Related]

  • 4. 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]

  • 5. PRINTR: prediction of RNA binding sites in proteins using SVM and profiles.
    Wang Y, Xue Z, Shen G, Xu J.
    Amino Acids; 2008 Aug 01; 35(2):295-302. PubMed ID: 18235992
    [Abstract] [Full Text] [Related]

  • 6. Using support vector machine to predict beta- and gamma-turns in proteins.
    Hu X, Li Q.
    J Comput Chem; 2008 Sep 01; 29(12):1867-75. PubMed ID: 18432623
    [Abstract] [Full Text] [Related]

  • 7. 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
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  • 9. 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
    [Abstract] [Full Text] [Related]

  • 10. A novel method for protein secondary structure prediction using dual-layer SVM and profiles.
    Guo J, Chen H, Sun Z, Lin Y.
    Proteins; 2004 Mar 01; 54(4):738-43. PubMed ID: 14997569
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  • 12. High accuracy prediction of beta-turns and their types using propensities and multiple alignments.
    Fuchs PF, Alix AJ.
    Proteins; 2005 Jun 01; 59(4):828-39. PubMed ID: 15822097
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  • 15. Beyond the Twilight Zone: automated prediction of structural properties of proteins by recursive neural networks and remote homology information.
    Mooney C, Pollastri G.
    Proteins; 2009 Oct 01; 77(1):181-90. PubMed ID: 19422056
    [Abstract] [Full Text] [Related]

  • 16. Predicting disulfide connectivity from protein sequence using multiple sequence feature vectors and secondary structure.
    Song J, Yuan Z, Tan H, Huber T, Burrage K.
    Bioinformatics; 2007 Dec 01; 23(23):3147-54. PubMed ID: 17942444
    [Abstract] [Full Text] [Related]

  • 17. 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]

  • 18. A novel method of protein secondary structure prediction with high segment overlap measure: support vector machine approach.
    Hua S, Sun Z.
    J Mol Biol; 2001 Apr 27; 308(2):397-407. PubMed ID: 11327775
    [Abstract] [Full Text] [Related]

  • 19. 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 27; 42(5):1749-55. PubMed ID: 21424809
    [Abstract] [Full Text] [Related]

  • 20. Protein secondary structure prediction with SPARROW.
    Bettella F, Rasinski D, Knapp EW.
    J Chem Inf Model; 2012 Feb 27; 52(2):545-56. PubMed ID: 22224407
    [Abstract] [Full Text] [Related]

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