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 *

286 related articles for article (PubMed ID: 31510679)

  • 21. DEPICTER2: a comprehensive webserver for intrinsic disorder and disorder function prediction.
    Basu S; Gsponer J; Kurgan L
    Nucleic Acids Res; 2023 Jul; 51(W1):W141-W147. PubMed ID: 37140058
    [TBL] [Abstract][Full Text] [Related]  

  • 22. RAPID: fast and accurate sequence-based prediction of intrinsic disorder content on proteomic scale.
    Yan J; Mizianty MJ; Filipow PL; Uversky VN; Kurgan L
    Biochim Biophys Acta; 2013 Aug; 1834(8):1671-80. PubMed ID: 23732563
    [TBL] [Abstract][Full Text] [Related]  

  • 23. DeepDISOBind: accurate prediction of RNA-, DNA- and protein-binding intrinsically disordered residues with deep multi-task learning.
    Zhang F; Zhao B; Shi W; Li M; Kurgan L
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34905768
    [TBL] [Abstract][Full Text] [Related]  

  • 24. High-throughput prediction of RNA, DNA and protein binding regions mediated by intrinsic disorder.
    Peng Z; Kurgan L
    Nucleic Acids Res; 2015 Oct; 43(18):e121. PubMed ID: 26109352
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Prediction of Disordered RNA, DNA, and Protein Binding Regions Using DisoRDPbind.
    Peng Z; Wang C; Uversky VN; Kurgan L
    Methods Mol Biol; 2017; 1484():187-203. PubMed ID: 27787828
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Prediction and analysis of nucleotide-binding residues using sequence and sequence-derived structural descriptors.
    Chen K; Mizianty MJ; Kurgan L
    Bioinformatics; 2012 Feb; 28(3):331-41. PubMed ID: 22130595
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Comprehensive review and empirical analysis of hallmarks of DNA-, RNA- and protein-binding residues in protein chains.
    Zhang J; Ma Z; Kurgan L
    Brief Bioinform; 2019 Jul; 20(4):1250-1268. PubMed ID: 29253082
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Improving the prediction of protein-nucleic acids binding residues via multiple sequence profiles and the consensus of complementary methods.
    Su H; Liu M; Sun S; Peng Z; Yang J
    Bioinformatics; 2019 Mar; 35(6):930-936. PubMed ID: 30169574
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Prediction of protein-RNA binding sites by a random forest method with combined features.
    Liu ZP; Wu LY; Wang Y; Zhang XS; Chen L
    Bioinformatics; 2010 Jul; 26(13):1616-22. PubMed ID: 20483814
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Structure-based prediction of protein- peptide binding regions using Random Forest.
    Taherzadeh G; Zhou Y; Liew AW; Yang Y
    Bioinformatics; 2018 Feb; 34(3):477-484. PubMed ID: 29028926
    [TBL] [Abstract][Full Text] [Related]  

  • 31. In Silico Prediction and Validation of Novel RNA Binding Proteins and Residues in the Human Proteome.
    Chowdhury S; Zhang J; Kurgan L
    Proteomics; 2018 Nov; 18(21-22):e1800064. PubMed ID: 29806170
    [TBL] [Abstract][Full Text] [Related]  

  • 32. GlycoMine: a machine learning-based approach for predicting N-, C- and O-linked glycosylation in the human proteome.
    Li F; Li C; Wang M; Webb GI; Zhang Y; Whisstock JC; Song J
    Bioinformatics; 2015 May; 31(9):1411-9. PubMed ID: 25568279
    [TBL] [Abstract][Full Text] [Related]  

  • 33. StackDPPred: a stacking based prediction of DNA-binding protein from sequence.
    Mishra A; Pokhrel P; Hoque MT
    Bioinformatics; 2019 Feb; 35(3):433-441. PubMed ID: 30032213
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Protein function annotation from sequence: prediction of residues interacting with RNA.
    Spriggs RV; Murakami Y; Nakamura H; Jones S
    Bioinformatics; 2009 Jun; 25(12):1492-7. PubMed ID: 19389733
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Computational Prediction of Intrinsic Disorder in Protein Sequences with the disCoP Meta-predictor.
    Oldfield CJ; Fan X; Wang C; Dunker AK; Kurgan L
    Methods Mol Biol; 2020; 2141():21-35. PubMed ID: 32696351
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Computational identification of binding energy hot spots in protein-RNA complexes using an ensemble approach.
    Pan Y; Wang Z; Zhan W; Deng L
    Bioinformatics; 2018 May; 34(9):1473-1480. PubMed ID: 29281004
    [TBL] [Abstract][Full Text] [Related]  

  • 37. XRRpred: accurate predictor of crystal structure quality from protein sequence.
    Ghadermarzi S; Krawczyk B; Song J; Kurgan L
    Bioinformatics; 2021 Dec; 37(23):4366-4374. PubMed ID: 34247234
    [TBL] [Abstract][Full Text] [Related]  

  • 38. MoRFpred, a computational tool for sequence-based prediction and characterization of short disorder-to-order transitioning binding regions in proteins.
    Disfani FM; Hsu WL; Mizianty MJ; Oldfield CJ; Xue B; Dunker AK; Uversky VN; Kurgan L
    Bioinformatics; 2012 Jun; 28(12):i75-83. PubMed ID: 22689782
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Prediction of Intrinsic Disorder with Quality Assessment Using QUARTER.
    Wu Z; Hu G; Oldfield CJ; Kurgan L
    Methods Mol Biol; 2020; 2165():83-101. PubMed ID: 32621220
    [TBL] [Abstract][Full Text] [Related]  

  • 40. CoMemMoRFPred: Sequence-based Prediction of MemMoRFs by Combining Predictors of Intrinsic Disorder, MoRFs and Disordered Lipid-binding Regions.
    Basu S; Hegedűs T; Kurgan L
    J Mol Biol; 2023 Nov; 435(21):168272. PubMed ID: 37709009
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 15.