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 *

191 related articles for article (PubMed ID: 33226061)

  • 21. DeepDTA: deep drug-target binding affinity prediction.
    Öztürk H; Özgür A; Ozkirimli E
    Bioinformatics; 2018 Sep; 34(17):i821-i829. PubMed ID: 30423097
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Binding affinity prediction for protein-ligand complex using deep attention mechanism based on intermolecular interactions.
    Seo S; Choi J; Park S; Ahn J
    BMC Bioinformatics; 2021 Nov; 22(1):542. PubMed ID: 34749664
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Automatic recognition of ligands in electron density by machine learning.
    Kowiel M; Brzezinski D; Porebski PJ; Shabalin IG; Jaskolski M; Minor W
    Bioinformatics; 2019 Feb; 35(3):452-461. PubMed ID: 30016407
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Machine Learning-Based Scoring Functions, Development and Applications with SAnDReS.
    Bitencourt-Ferreira G; Rizzotto C; de Azevedo Junior WF
    Curr Med Chem; 2021; 28(9):1746-1756. PubMed ID: 32410551
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Nonparametric chemical descriptors for the calculation of ligand-biopolymer affinities with machine-learning scoring functions.
    Moman E; Grishina MA; Potemkin VA
    J Comput Aided Mol Des; 2019 Nov; 33(11):943-953. PubMed ID: 31728812
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Protein-ligand binding affinity prediction exploiting sequence constituent homology.
    Abdel-Rehim A; Orhobor O; Hang L; Ni H; King RD
    Bioinformatics; 2023 Aug; 39(8):. PubMed ID: 37572302
    [TBL] [Abstract][Full Text] [Related]  

  • 27. The Impact of Crystallographic Data for the Development of Machine Learning Models to Predict Protein-Ligand Binding Affinity.
    Veit-Acosta M; de Azevedo Junior WF
    Curr Med Chem; 2021 Oct; 28(34):7006-7022. PubMed ID: 33568025
    [TBL] [Abstract][Full Text] [Related]  

  • 28. GB-score: Minimally designed machine learning scoring function based on distance-weighted interatomic contact features.
    Rayka M; Firouzi R
    Mol Inform; 2023 Mar; 42(3):e2200135. PubMed ID: 36722733
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Structural and Sequence Similarity Makes a Significant Impact on Machine-Learning-Based Scoring Functions for Protein-Ligand Interactions.
    Li Y; Yang J
    J Chem Inf Model; 2017 Apr; 57(4):1007-1012. PubMed ID: 28358210
    [TBL] [Abstract][Full Text] [Related]  

  • 30. PharmRF: A machine-learning scoring function to identify the best protein-ligand complexes for structure-based pharmacophore screening with high enrichments.
    Kumar SP; Dixit NY; Patel CN; Rawal RM; Pandya HA
    J Comput Chem; 2022 May; 43(12):847-863. PubMed ID: 35301752
    [TBL] [Abstract][Full Text] [Related]  

  • 31. CAPLA: improved prediction of protein-ligand binding affinity by a deep learning approach based on a cross-attention mechanism.
    Jin Z; Wu T; Chen T; Pan D; Wang X; Xie J; Quan L; Lyu Q
    Bioinformatics; 2023 Feb; 39(2):. PubMed ID: 36688724
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Machine learning accelerates MD-based binding pose prediction between ligands and proteins.
    Terayama K; Iwata H; Araki M; Okuno Y; Tsuda K
    Bioinformatics; 2018 Mar; 34(5):770-778. PubMed ID: 29040432
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Machine learning in computational docking.
    Khamis MA; Gomaa W; Ahmed WF
    Artif Intell Med; 2015 Mar; 63(3):135-52. PubMed ID: 25724101
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Descriptor Data Bank (DDB): A Cloud Platform for Multiperspective Modeling of Protein-Ligand Interactions.
    Ashtawy HM; Mahapatra NR
    J Chem Inf Model; 2018 Jan; 58(1):134-147. PubMed ID: 29186950
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Leveraging scaffold information to predict protein-ligand binding affinity with an empirical graph neural network.
    Xia C; Feng SH; Xia Y; Pan X; Shen HB
    Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36627113
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Taba: A Tool to Analyze the Binding Affinity.
    da Silva AD; Bitencourt-Ferreira G; de Azevedo WF
    J Comput Chem; 2020 Jan; 41(1):69-73. PubMed ID: 31410856
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Machine Learning to Predict Binding Affinity.
    Bitencourt-Ferreira G; de Azevedo WF
    Methods Mol Biol; 2019; 2053():251-273. PubMed ID: 31452110
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Structure-based protein-ligand interaction fingerprints for binding affinity prediction.
    Wang DD; Chan MT; Yan H
    Comput Struct Biotechnol J; 2021; 19():6291-6300. PubMed ID: 34900139
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Tapping on the Black Box: How Is the Scoring Power of a Machine-Learning Scoring Function Dependent on the Training Set?
    Su M; Feng G; Liu Z; Li Y; Wang R
    J Chem Inf Model; 2020 Mar; 60(3):1122-1136. PubMed ID: 32085675
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Improving the binding affinity estimations of protein-ligand complexes using machine-learning facilitated force field method.
    Soni A; Bhat R; Jayaram B
    J Comput Aided Mol Des; 2020 Aug; 34(8):817-830. PubMed ID: 32185583
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 10.