BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

173 related articles for article (PubMed ID: 24303019)

  • 1. Detecting protein candidate fragments using a structural alphabet profile comparison approach.
    Shen Y; Picord G; Guyon F; Tuffery P
    PLoS One; 2013; 8(11):e80493. PubMed ID: 24303019
    [TBL] [Abstract][Full Text] [Related]  

  • 2. PEP-FOLD: an online resource for de novo peptide structure prediction.
    Maupetit J; Derreumaux P; Tuffery P
    Nucleic Acids Res; 2009 Jul; 37(Web Server issue):W498-503. PubMed ID: 19433514
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Use of a structural alphabet to find compatible folds for amino acid sequences.
    Mahajan S; de Brevern AG; Sanejouand YH; Srinivasan N; Offmann B
    Protein Sci; 2015 Jan; 24(1):145-53. PubMed ID: 25297700
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Combining evolutionary and structural information for local protein structure prediction.
    Pei J; Grishin NV
    Proteins; 2004 Sep; 56(4):782-94. PubMed ID: 15281130
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Improving protein fold recognition with hybrid profiles combining sequence and structure evolution.
    Ghouzam Y; Postic G; de Brevern AG; Gelly JC
    Bioinformatics; 2015 Dec; 31(23):3782-9. PubMed ID: 26254434
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Building a better fragment library for de novo protein structure prediction.
    de Oliveira SH; Shi J; Deane CM
    PLoS One; 2015; 10(4):e0123998. PubMed ID: 25901595
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Extension of a local backbone description using a structural alphabet: a new approach to the sequence-structure relationship.
    de Brevern AG; Valadié H; Hazout S; Etchebest C
    Protein Sci; 2002 Dec; 11(12):2871-86. PubMed ID: 12441385
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Methods for optimizing the structure alphabet sequences of proteins.
    Dong QW; Wang XL; Lin L
    Comput Biol Med; 2007 Nov; 37(11):1610-6. PubMed ID: 17493604
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Direct prediction of profiles of sequences compatible with a protein structure by neural networks with fragment-based local and energy-based nonlocal profiles.
    Li Z; Yang Y; Faraggi E; Zhan J; Zhou Y
    Proteins; 2014 Oct; 82(10):2565-73. PubMed ID: 24898915
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Fast protein fragment similarity scoring using a Binet-Cauchy kernel.
    Guyon F; Tufféry P
    Bioinformatics; 2014 Mar; 30(6):784-91. PubMed ID: 24167157
    [TBL] [Abstract][Full Text] [Related]  

  • 11. "Pinning strategy": a novel approach for predicting the backbone structure in terms of protein blocks from sequence.
    De Brevern AG; Etchebest C; Benros C; Hazout S
    J Biosci; 2007 Jan; 32(1):51-70. PubMed ID: 17426380
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Incorporation of local structural preference potential improves fold recognition.
    Hu Y; Dong X; Wu A; Cao Y; Tian L; Jiang T
    PLoS One; 2011 Feb; 6(2):e17215. PubMed ID: 21365008
    [TBL] [Abstract][Full Text] [Related]  

  • 13. BCSearch: fast structural fragment mining over large collections of protein structures.
    Guyon F; Martz F; Vavrusa M; Bécot J; Rey J; Tufféry P
    Nucleic Acids Res; 2015 Jul; 43(W1):W378-82. PubMed ID: 25977292
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Mining protein loops using a structural alphabet and statistical exceptionality.
    Regad L; Martin J; Nuel G; Camproux AC
    BMC Bioinformatics; 2010 Feb; 11():75. PubMed ID: 20132552
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 'Hybrid protein model' for optimally defining 3D protein structure fragments.
    de Brevern AG; Hazout S
    Bioinformatics; 2003 Feb; 19(3):345-53. PubMed ID: 12584119
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Automated alphabet reduction for protein datasets.
    Bacardit J; Stout M; Hirst JD; Valencia A; Smith RE; Krasnogor N
    BMC Bioinformatics; 2009 Jan; 10():6. PubMed ID: 19126227
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model.
    Wang S; Sun S; Li Z; Zhang R; Xu J
    PLoS Comput Biol; 2017 Jan; 13(1):e1005324. PubMed ID: 28056090
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Fold recognition by combining sequence profiles derived from evolution and from depth-dependent structural alignment of fragments.
    Zhou H; Zhou Y
    Proteins; 2005 Feb; 58(2):321-8. PubMed ID: 15523666
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Enhanced protein fold recognition using a structural alphabet.
    Deschavanne P; Tufféry P
    Proteins; 2009 Jul; 76(1):129-37. PubMed ID: 19089985
    [TBL] [Abstract][Full Text] [Related]  

  • 20. The dual role of fragments in fragment-assembly methods for de novo protein structure prediction.
    Handl J; Knowles J; Vernon R; Baker D; Lovell SC
    Proteins; 2012 Feb; 80(2):490-504. PubMed ID: 22095594
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.