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 *

213 related articles for article (PubMed ID: 28334201)

  • 1. Critical evaluation of bioinformatics tools for the prediction of protein crystallization propensity.
    Wang H; Feng L; Webb GI; Kurgan L; Song J; Lin D
    Brief Bioinform; 2018 Sep; 19(5):838-852. PubMed ID: 28334201
    [TBL] [Abstract][Full Text] [Related]  

  • 2. PredPPCrys: accurate prediction of sequence cloning, protein production, purification and crystallization propensity from protein sequences using multi-step heterogeneous feature fusion and selection.
    Wang H; Wang M; Tan H; Li Y; Zhang Z; Song J
    PLoS One; 2014; 9(8):e105902. PubMed ID: 25148528
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Accurate multistage prediction of protein crystallization propensity using deep-cascade forest with sequence-based features.
    Zhu YH; Hu J; Ge F; Li F; Song J; Zhang Y; Yu DJ
    Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32436937
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Survey of Predictors of Propensity for Protein Production and Crystallization with Application to Predict Resolution of Crystal Structures.
    Gao J; Wu Z; Hu G; Wang K; Song J; Joachimiak A; Kurgan L
    Curr Protein Pept Sci; 2018; 19(2):200-210. PubMed ID: 28933304
    [TBL] [Abstract][Full Text] [Related]  

  • 5. fDETECT webserver: fast predictor of propensity for protein production, purification, and crystallization.
    Meng F; Wang C; Kurgan L
    BMC Bioinformatics; 2018 Jan; 18(1):580. PubMed ID: 29295714
    [TBL] [Abstract][Full Text] [Related]  

  • 6. CLPred: a sequence-based protein crystallization predictor using BLSTM neural network.
    Xuan W; Liu N; Huang N; Li Y; Wang J
    Bioinformatics; 2020 Dec; 36(Suppl_2):i709-i717. PubMed ID: 33381840
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Computational approaches to selecting and optimising targets for structural biology.
    Overton IM; Barton GJ
    Methods; 2011 Sep; 55(1):3-11. PubMed ID: 21906678
    [TBL] [Abstract][Full Text] [Related]  

  • 8. DeepCrystal: a deep learning framework for sequence-based protein crystallization prediction.
    Elbasir A; Moovarkumudalvan B; Kunji K; Kolatkar PR; Mall R; Bensmail H
    Bioinformatics; 2019 Jul; 35(13):2216-2225. PubMed ID: 30462171
    [TBL] [Abstract][Full Text] [Related]  

  • 9. RFCRYS: sequence-based protein crystallization propensity prediction by means of random forest.
    Jahandideh S; Mahdavi A
    J Theor Biol; 2012 Aug; 306():115-9. PubMed ID: 22726810
    [TBL] [Abstract][Full Text] [Related]  

  • 10. GCmapCrys: Integrating graph attention network with predicted contact map for multi-stage protein crystallization propensity prediction.
    Wang PH; Zhu YH; Yang X; Yu DJ
    Anal Biochem; 2023 Feb; 663():115020. PubMed ID: 36521558
    [TBL] [Abstract][Full Text] [Related]  

  • 11. CRYSpred: accurate sequence-based protein crystallization propensity prediction using sequence-derived structural characteristics.
    Mizianty MJ; Kurgan LA
    Protein Pept Lett; 2012 Jan; 19(1):40-9. PubMed ID: 21919861
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Crysalis: an integrated server for computational analysis and design of protein crystallization.
    Wang H; Feng L; Zhang Z; Webb GI; Lin D; Song J
    Sci Rep; 2016 Feb; 6():21383. PubMed ID: 26906024
    [TBL] [Abstract][Full Text] [Related]  

  • 13. XANNpred: neural nets that predict the propensity of a protein to yield diffraction-quality crystals.
    Overton IM; van Niekerk CA; Barton GJ
    Proteins; 2011 Apr; 79(4):1027-33. PubMed ID: 21246630
    [TBL] [Abstract][Full Text] [Related]  

  • 14. SVMCRYS: an SVM approach for the prediction of protein crystallization propensity from protein sequence.
    Kandaswamy KK; Pugalenthi G; Suganthan PN; Gangal R
    Protein Pept Lett; 2010 Apr; 17(4):423-30. PubMed ID: 20044918
    [TBL] [Abstract][Full Text] [Related]  

  • 15. BCrystal: an interpretable sequence-based protein crystallization predictor.
    Elbasir A; Mall R; Kunji K; Rawi R; Islam Z; Chuang GY; Kolatkar PR; Bensmail H
    Bioinformatics; 2020 Mar; 36(5):1429-1438. PubMed ID: 31603511
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Meta prediction of protein crystallization propensity.
    Mizianty MJ; Kurgan L
    Biochem Biophys Res Commun; 2009 Dec; 390(1):10-5. PubMed ID: 19755114
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Sequence-based prediction of protein crystallization, purification and production propensity.
    Mizianty MJ; Kurgan L
    Bioinformatics; 2011 Jul; 27(13):i24-33. PubMed ID: 21685077
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Towards more accurate prediction of protein folding rates: a review of the existing Web-based bioinformatics approaches.
    Chang CC; Tey BT; Song J; Ramanan RN
    Brief Bioinform; 2015 Mar; 16(2):314-24. PubMed ID: 24621527
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Enhanced crystallizability by protein engineering approaches: a general overview.
    Ruggiero A; Smaldone G; Squeglia F; Berisio R
    Protein Pept Lett; 2012 Jul; 19(7):732-42. PubMed ID: 22489782
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Life in the fast lane for protein crystallization and X-ray crystallography.
    Pusey ML; Liu ZJ; Tempel W; Praissman J; Lin D; Wang BC; Gavira JA; Ng JD
    Prog Biophys Mol Biol; 2005 Jul; 88(3):359-86. PubMed ID: 15652250
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.