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Journal Abstract Search

1068 related items for PubMed ID: 18632749

  • 1. Accurate prediction of stability changes in protein mutants by combining machine learning with structure based computational mutagenesis.
    Masso M, Vaisman II.
    Bioinformatics; 2008 Sep 15; 24(18):2002-9. PubMed ID: 18632749
    [Abstract] [Full Text] [Related]

  • 2. Accurate prediction of enzyme mutant activity based on a multibody statistical potential.
    Masso M, Vaisman II.
    Bioinformatics; 2007 Dec 01; 23(23):3155-61. PubMed ID: 17977887
    [Abstract] [Full Text] [Related]

  • 3. Statistical geometry based prediction of nonsynonymous SNP functional effects using random forest and neuro-fuzzy classifiers.
    Barenboim M, Masso M, Vaisman II, Jamison DC.
    Proteins; 2008 Jun 01; 71(4):1930-9. PubMed ID: 18186470
    [Abstract] [Full Text] [Related]

  • 4. A neural-network-based method for predicting protein stability changes upon single point mutations.
    Capriotti E, Fariselli P, Casadio R.
    Bioinformatics; 2004 Aug 04; 20 Suppl 1():i63-8. PubMed ID: 15262782
    [Abstract] [Full Text] [Related]

  • 5. Knowledge-based computational mutagenesis for predicting the disease potential of human non-synonymous single nucleotide polymorphisms.
    Masso M, Vaisman II.
    J Theor Biol; 2010 Oct 21; 266(4):560-8. PubMed ID: 20655929
    [Abstract] [Full Text] [Related]

  • 6. Prediction of protein mutant stability using classification and regression tool.
    Huang LT, Saraboji K, Ho SY, Hwang SF, Ponnuswamy MN, Gromiha MM.
    Biophys Chem; 2007 Feb 21; 125(2-3):462-70. PubMed ID: 17113702
    [Abstract] [Full Text] [Related]

  • 7. Predicting protein stability changes from sequences using support vector machines.
    Capriotti E, Fariselli P, Calabrese R, Casadio R.
    Bioinformatics; 2005 Sep 01; 21 Suppl 2():ii54-8. PubMed ID: 16204125
    [Abstract] [Full Text] [Related]

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  • 9. 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]

  • 10. HYPROSP II--a knowledge-based hybrid method for protein secondary structure prediction based on local prediction confidence.
    Lin HN, Chang JM, Wu KP, Sung TY, Hsu WL.
    Bioinformatics; 2005 Aug 01; 21(15):3227-33. PubMed ID: 15932901
    [Abstract] [Full Text] [Related]

  • 11. Fast and accurate predictions of protein stability changes upon mutations using statistical potentials and neural networks: PoPMuSiC-2.0.
    Dehouck Y, Grosfils A, Folch B, Gilis D, Bogaerts P, Rooman M.
    Bioinformatics; 2009 Oct 01; 25(19):2537-43. PubMed ID: 19654118
    [Abstract] [Full Text] [Related]

  • 12. Protein structure prediction based on sequence similarity.
    Jaroszewski L.
    Methods Mol Biol; 2009 Oct 01; 569():129-56. PubMed ID: 19623489
    [Abstract] [Full Text] [Related]

  • 13. Accurate prediction for atomic-level protein design and its application in diversifying the near-optimal sequence space.
    Fromer M, Yanover C.
    Proteins; 2009 May 15; 75(3):682-705. PubMed ID: 19003998
    [Abstract] [Full Text] [Related]

  • 14. Predicting protein secondary structure by a support vector machine based on a new coding scheme.
    Wang LH, Liu J, Li YF, Zhou HB.
    Genome Inform; 2004 May 15; 15(2):181-90. PubMed ID: 15706504
    [Abstract] [Full Text] [Related]

  • 15. Robust prediction of mutation-induced protein stability change by property encoding of amino acids.
    Kang S, Chen G, Xiao G.
    Protein Eng Des Sel; 2009 Feb 15; 22(2):75-83. PubMed ID: 19054789
    [Abstract] [Full Text] [Related]

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  • 17. Assessing computational methods for predicting protein stability upon mutation: good on average but not in the details.
    Potapov V, Cohen M, Schreiber G.
    Protein Eng Des Sel; 2009 Sep 15; 22(9):553-60. PubMed ID: 19561092
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  • 19. Pairwise covariance adds little to secondary structure prediction but improves the prediction of non-canonical local structure.
    Bystroff C, Webb-Robertson BJ.
    BMC Bioinformatics; 2008 Oct 10; 9():429. PubMed ID: 18847485
    [Abstract] [Full Text] [Related]

  • 20. Analysis of covariation in an SH3 domain sequence alignment: applications in tertiary contact prediction and the design of compensating hydrophobic core substitutions.
    Larson SM, Di Nardo AA, Davidson AR.
    J Mol Biol; 2000 Oct 27; 303(3):433-46. PubMed ID: 11031119
    [Abstract] [Full Text] [Related]

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