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: 28865433)

  • 1. RRCRank: a fusion method using rank strategy for residue-residue contact prediction.
    Jing X; Dong Q; Lu R
    BMC Bioinformatics; 2017 Sep; 18(1):390. PubMed ID: 28865433
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Protein contact prediction by integrating deep multiple sequence alignments, coevolution and machine learning.
    Adhikari B; Hou J; Cheng J
    Proteins; 2018 Mar; 86 Suppl 1(Suppl 1):84-96. PubMed ID: 29047157
    [TBL] [Abstract][Full Text] [Related]  

  • 3. R2C: improving ab initio residue contact map prediction using dynamic fusion strategy and Gaussian noise filter.
    Yang J; Jin QY; Zhang B; Shen HB
    Bioinformatics; 2016 Aug; 32(16):2435-43. PubMed ID: 27153618
    [TBL] [Abstract][Full Text] [Related]  

  • 4. DNCON2: improved protein contact prediction using two-level deep convolutional neural networks.
    Adhikari B; Hou J; Cheng J
    Bioinformatics; 2018 May; 34(9):1466-1472. PubMed ID: 29228185
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Predicting protein residue-residue contacts using random forests and deep networks.
    Luttrell J; Liu T; Zhang C; Wang Z
    BMC Bioinformatics; 2019 Mar; 20(Suppl 2):100. PubMed ID: 30871477
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. FingerprintContacts: Predicting Alternative Conformations of Proteins from Coevolution.
    Feng J; Shukla D
    J Phys Chem B; 2020 May; 124(18):3605-3615. PubMed ID: 32283936
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Identification of residue pairing in interacting β-strands from a predicted residue contact map.
    Mao W; Wang T; Zhang W; Gong H
    BMC Bioinformatics; 2018 Apr; 19(1):146. PubMed ID: 29673311
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Deep learning methods for protein torsion angle prediction.
    Li H; Hou J; Adhikari B; Lyu Q; Cheng J
    BMC Bioinformatics; 2017 Sep; 18(1):417. PubMed ID: 28923002
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Assessment of contact predictions in CASP12: Co-evolution and deep learning coming of age.
    Schaarschmidt J; Monastyrskyy B; Kryshtafovych A; Bonvin AMJJ
    Proteins; 2018 Mar; 86 Suppl 1(Suppl Suppl 1):51-66. PubMed ID: 29071738
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Predicting protein inter-residue contacts using composite likelihood maximization and deep learning.
    Zhang H; Zhang Q; Ju F; Zhu J; Gao Y; Xie Z; Deng M; Sun S; Zheng WM; Bu D
    BMC Bioinformatics; 2019 Oct; 20(1):537. PubMed ID: 31664895
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Sorting protein decoys by machine-learning-to-rank.
    Jing X; Wang K; Lu R; Dong Q
    Sci Rep; 2016 Aug; 6():31571. PubMed ID: 27530967
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Improving residue-residue contact prediction via low-rank and sparse decomposition of residue correlation matrix.
    Zhang H; Gao Y; Deng M; Wang C; Zhu J; Li SC; Zheng WM; Bu D
    Biochem Biophys Res Commun; 2016 Mar; 472(1):217-22. PubMed ID: 26920058
    [TBL] [Abstract][Full Text] [Related]  

  • 14. DeepConPred2: An Improved Method for the Prediction of Protein Residue Contacts.
    Ding W; Mao W; Shao D; Zhang W; Gong H
    Comput Struct Biotechnol J; 2018; 16():503-510. PubMed ID: 30505403
    [TBL] [Abstract][Full Text] [Related]  

  • 15. CONFOLD2: improved contact-driven ab initio protein structure modeling.
    Adhikari B; Cheng J
    BMC Bioinformatics; 2018 Jan; 19(1):22. PubMed ID: 29370750
    [TBL] [Abstract][Full Text] [Related]  

  • 16. MemBrain-contact 2.0: a new two-stage machine learning model for the prediction enhancement of transmembrane protein residue contacts in the full chain.
    Yang J; Shen HB
    Bioinformatics; 2018 Jan; 34(2):230-238. PubMed ID: 28968641
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A further leap of improvement in tertiary structure prediction in CASP13 prompts new routes for future assessments.
    Abriata LA; Tamò GE; Dal Peraro M
    Proteins; 2019 Dec; 87(12):1100-1112. PubMed ID: 31344267
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Protein Secondary Structure Prediction Based on Data Partition and Semi-Random Subspace Method.
    Ma Y; Liu Y; Cheng J
    Sci Rep; 2018 Jun; 8(1):9856. PubMed ID: 29959372
    [TBL] [Abstract][Full Text] [Related]  

  • 19. New Labeling Methods for Deep Learning Real-Valued Inter-Residue Distance Prediction.
    Barger J; Adhikari B
    IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(6):3586-3594. PubMed ID: 34559660
    [TBL] [Abstract][Full Text] [Related]  

  • 20. COUSCOus: improved protein contact prediction using an empirical Bayes covariance estimator.
    Rawi R; Mall R; Kunji K; El Anbari M; Aupetit M; Ullah E; Bensmail H
    BMC Bioinformatics; 2016 Dec; 17(1):533. PubMed ID: 27978812
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.