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 *

279 related articles for article (PubMed ID: 35142086)

  • 21. RmsdXNA: RMSD prediction of nucleic acid-ligand docking poses using machine-learning method.
    Tan LH; Kwoh CK; Mu Y
    Brief Bioinform; 2024 Mar; 25(3):. PubMed ID: 38695120
    [TBL] [Abstract][Full Text] [Related]  

  • 22. MetaScore: A Novel Machine-Learning-Based Approach to Improve Traditional Scoring Functions for Scoring Protein-Protein Docking Conformations.
    Jung Y; Geng C; Bonvin AMJJ; Xue LC; Honavar VG
    Biomolecules; 2023 Jan; 13(1):. PubMed ID: 36671507
    [TBL] [Abstract][Full Text] [Related]  

  • 23. A Hybrid Docking and Machine Learning Approach to Enhance the Performance of Virtual Screening Carried out on Protein-Protein Interfaces.
    Singh N; Villoutreix BO
    Int J Mol Sci; 2022 Nov; 23(22):. PubMed ID: 36430841
    [TBL] [Abstract][Full Text] [Related]  

  • 24. An Overview of Scoring Functions Used for Protein-Ligand Interactions in Molecular Docking.
    Li J; Fu A; Zhang L
    Interdiscip Sci; 2019 Jun; 11(2):320-328. PubMed ID: 30877639
    [TBL] [Abstract][Full Text] [Related]  

  • 25. ET-score: Improving Protein-ligand Binding Affinity Prediction Based on Distance-weighted Interatomic Contact Features Using Extremely Randomized Trees Algorithm.
    Rayka M; Karimi-Jafari MH; Firouzi R
    Mol Inform; 2021 Aug; 40(8):e2060084. PubMed ID: 34021703
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Energy-based graph convolutional networks for scoring protein docking models.
    Cao Y; Shen Y
    Proteins; 2020 Aug; 88(8):1091-1099. PubMed ID: 32144844
    [TBL] [Abstract][Full Text] [Related]  

  • 27. The impact of cross-docked poses on performance of machine learning classifier for protein-ligand binding pose prediction.
    Shen C; Hu X; Gao J; Zhang X; Zhong H; Wang Z; Xu L; Kang Y; Cao D; Hou T
    J Cheminform; 2021 Oct; 13(1):81. PubMed ID: 34656169
    [TBL] [Abstract][Full Text] [Related]  

  • 28. BgN-Score and BsN-Score: bagging and boosting based ensemble neural networks scoring functions for accurate binding affinity prediction of protein-ligand complexes.
    Ashtawy HM; Mahapatra NR
    BMC Bioinformatics; 2015; 16 Suppl 4(Suppl 4):S8. PubMed ID: 25734685
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Binding affinity prediction for protein-ligand complexes based on β contacts and B factor.
    Liu Q; Kwoh CK; Li J
    J Chem Inf Model; 2013 Nov; 53(11):3076-85. PubMed ID: 24191692
    [TBL] [Abstract][Full Text] [Related]  

  • 30. RNAPosers: Machine Learning Classifiers for Ribonucleic Acid-Ligand Poses.
    Chhabra S; Xie J; Frank AT
    J Phys Chem B; 2020 Jun; 124(22):4436-4445. PubMed ID: 32427491
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Scoring functions for prediction of protein-ligand interactions.
    Wang JC; Lin JH
    Curr Pharm Des; 2013; 19(12):2174-82. PubMed ID: 23016847
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Empirical Scoring Functions for Affinity Prediction of Protein-ligand Complexes.
    Pason LP; Sotriffer CA
    Mol Inform; 2016 Dec; 35(11-12):541-548. PubMed ID: 27870243
    [TBL] [Abstract][Full Text] [Related]  

  • 33. A comparative assessment of ranking accuracies of conventional and machine-learning-based scoring functions for protein-ligand binding affinity prediction.
    Ashtawy HM; Mahapatra NR
    IEEE/ACM Trans Comput Biol Bioinform; 2012; 9(5):1301-13. PubMed ID: 22411892
    [TBL] [Abstract][Full Text] [Related]  

  • 34. A fully differentiable ligand pose optimization framework guided by deep learning and a traditional scoring function.
    Wang Z; Zheng L; Wang S; Lin M; Wang Z; Kong AW; Mu Y; Wei Y; Li W
    Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36502369
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Dowker complex based machine learning (DCML) models for protein-ligand binding affinity prediction.
    Liu X; Feng H; Wu J; Xia K
    PLoS Comput Biol; 2022 Apr; 18(4):e1009943. PubMed ID: 35385478
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Machine Learning Scoring Functions for Drug Discovery from Experimental and Computer-Generated Protein-Ligand Structures: Towards Per-Target Scoring Functions.
    Pellicani F; Dal Ben D; Perali A; Pilati S
    Molecules; 2023 Feb; 28(4):. PubMed ID: 36838647
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Sfcnn: a novel scoring function based on 3D convolutional neural network for accurate and stable protein-ligand affinity prediction.
    Wang Y; Wei Z; Xi L
    BMC Bioinformatics; 2022 Jun; 23(1):222. PubMed ID: 35676617
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Are predefined decoy sets of ligand poses able to quantify scoring function accuracy?
    Korb O; Ten Brink T; Victor Paul Raj FR; Keil M; Exner TE
    J Comput Aided Mol Des; 2012 Feb; 26(2):185-97. PubMed ID: 22231069
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Evaluation of several two-step scoring functions based on linear interaction energy, effective ligand size, and empirical pair potentials for prediction of protein-ligand binding geometry and free energy.
    Rahaman O; Estrada TP; Doren DJ; Taufer M; Brooks CL; Armen RS
    J Chem Inf Model; 2011 Sep; 51(9):2047-65. PubMed ID: 21644546
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Protein-ligand binding affinity prediction model based on graph attention network.
    Yuan H; Huang J; Li J
    Math Biosci Eng; 2021 Oct; 18(6):9148-9162. PubMed ID: 34814340
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 14.