These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

128 related articles for article (PubMed ID: 17238841)

  • 1. Predicting disordered regions in proteins based on decision trees of reduced amino acid composition.
    Han P; Zhang X; Norton RS; Feng ZP
    J Comput Biol; 2006 Dec; 13(10):1723-34. PubMed ID: 17238841
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Prediction of unfolded segments in a protein sequence based on amino acid composition.
    Coeytaux K; Poupon A
    Bioinformatics; 2005 May; 21(9):1891-900. PubMed ID: 15657106
    [TBL] [Abstract][Full Text] [Related]  

  • 3. IUPred: web server for the prediction of intrinsically unstructured regions of proteins based on estimated energy content.
    Dosztányi Z; Csizmok V; Tompa P; Simon I
    Bioinformatics; 2005 Aug; 21(16):3433-4. PubMed ID: 15955779
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Predicting disordered regions in proteins using the profiles of amino acid indices.
    Han P; Zhang X; Feng ZP
    BMC Bioinformatics; 2009 Jan; 10 Suppl 1(Suppl 1):S42. PubMed ID: 19208144
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Large-scale prediction of long disordered regions in proteins using random forests.
    Han P; Zhang X; Norton RS; Feng ZP
    BMC Bioinformatics; 2009 Jan; 10():8. PubMed ID: 19128505
    [TBL] [Abstract][Full Text] [Related]  

  • 6. POODLE-L: a two-level SVM prediction system for reliably predicting long disordered regions.
    Hirose S; Shimizu K; Kanai S; Kuroda Y; Noguchi T
    Bioinformatics; 2007 Aug; 23(16):2046-53. PubMed ID: 17545177
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A machine learning based method for the prediction of secretory proteins using amino acid composition, their order and similarity-search.
    Garg A; Raghava GP
    In Silico Biol; 2008; 8(2):129-40. PubMed ID: 18928201
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Prediction of disordered regions in proteins based on the meta approach.
    Ishida T; Kinoshita K
    Bioinformatics; 2008 Jun; 24(11):1344-8. PubMed ID: 18426805
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Intrinsic disorder in the Protein Data Bank.
    Le Gall T; Romero PR; Cortese MS; Uversky VN; Dunker AK
    J Biomol Struct Dyn; 2007 Feb; 24(4):325-42. PubMed ID: 17206849
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Genome-scale prediction of proteins with long intrinsically disordered regions.
    Peng Z; Mizianty MJ; Kurgan L
    Proteins; 2014 Jan; 82(1):145-58. PubMed ID: 23798504
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Length-dependent prediction of protein intrinsic disorder.
    Peng K; Radivojac P; Vucetic S; Dunker AK; Obradovic Z
    BMC Bioinformatics; 2006 Apr; 7():208. PubMed ID: 16618368
    [TBL] [Abstract][Full Text] [Related]  

  • 12. POODLE-I: disordered region prediction by integrating POODLE series and structural information predictors based on a workflow approach.
    Hirose S; Shimizu K; Noguchi T
    In Silico Biol; 2010; 10(3):185-91. PubMed ID: 22430291
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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; 71(4):1930-9. PubMed ID: 18186470
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Reduced amino acid alphabet is sufficient to accurately recognize intrinsically disordered protein.
    Weathers EA; Paulaitis ME; Woolf TB; Hoh JH
    FEBS Lett; 2004 Oct; 576(3):348-52. PubMed ID: 15498561
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Comparing and combining predictors of mostly disordered proteins.
    Oldfield CJ; Cheng Y; Cortese MS; Brown CJ; Uversky VN; Dunker AK
    Biochemistry; 2005 Feb; 44(6):1989-2000. PubMed ID: 15697224
    [TBL] [Abstract][Full Text] [Related]  

  • 16. POODLE-S: web application for predicting protein disorder by using physicochemical features and reduced amino acid set of a position-specific scoring matrix.
    Shimizu K; Hirose S; Noguchi T
    Bioinformatics; 2007 Sep; 23(17):2337-8. PubMed ID: 17599940
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Predicting intrinsic disorder from amino acid sequence.
    Obradovic Z; Peng K; Vucetic S; Radivojac P; Brown CJ; Dunker AK
    Proteins; 2003; 53 Suppl 6():566-72. PubMed ID: 14579347
    [TBL] [Abstract][Full Text] [Related]  

  • 18. DisoMCS: Accurately Predicting Protein Intrinsically Disordered Regions Using a Multi-Class Conservative Score Approach.
    Wang Z; Yang Q; Li T; Cong P
    PLoS One; 2015; 10(6):e0128334. PubMed ID: 26090958
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Uncertainty analysis in protein disorder prediction.
    Ghalwash MF; Dunker AK; Obradović Z
    Mol Biosyst; 2012 Jan; 8(1):381-91. PubMed ID: 22101336
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Correlation and prediction of gene expression level from amino acid and dipeptide composition of its protein.
    Raghava GP; Han JH
    BMC Bioinformatics; 2005 Mar; 6():59. PubMed ID: 15773999
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.