BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

115 related articles for article (PubMed ID: 36108270)

  • 1. EISA-Score: Element Interactive Surface Area Score for Protein-Ligand Binding Affinity Prediction.
    Rana MM; Nguyen DD
    J Chem Inf Model; 2022 Sep; 62(18):4329-4341. PubMed ID: 36108270
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Persistent spectral hypergraph based machine learning (PSH-ML) for protein-ligand binding affinity prediction.
    Liu X; Feng H; Wu J; Xia K
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33837771
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. 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]  

  • 5. 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]  

  • 6. Boosted neural networks scoring functions for accurate ligand docking and ranking.
    Ashtawy HM; Mahapatra NR
    J Bioinform Comput Biol; 2018 Apr; 16(2):1850004. PubMed ID: 29495922
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Geometric graph learning with extended atom-types features for protein-ligand binding affinity prediction.
    Rana MM; Nguyen DD
    Comput Biol Med; 2023 Sep; 164():107250. PubMed ID: 37515872
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Learning from the ligand: using ligand-based features to improve binding affinity prediction.
    Boyles F; Deane CM; Morris GM
    Bioinformatics; 2020 Feb; 36(3):758-764. PubMed ID: 31598630
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. Persistent Path-Spectral (PPS) Based Machine Learning for Protein-Ligand Binding Affinity Prediction.
    Liu R; Liu X; Wu J
    J Chem Inf Model; 2023 Feb; 63(3):1066-1075. PubMed ID: 36647267
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking.
    Ballester PJ; Mitchell JB
    Bioinformatics; 2010 May; 26(9):1169-75. PubMed ID: 20236947
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. A Comparative Assessment of Predictive Accuracies of Conventional and Machine Learning Scoring Functions for Protein-Ligand Binding Affinity Prediction.
    Ashtawy HM; Mahapatra NR
    IEEE/ACM Trans Comput Biol Bioinform; 2015; 12(2):335-47. PubMed ID: 26357221
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Computationally predicting binding affinity in protein-ligand complexes: free energy-based simulations and machine learning-based scoring functions.
    Wang DD; Zhu M; Yan H
    Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32591817
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. 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]  

  • 17. ID-Score: a new empirical scoring function based on a comprehensive set of descriptors related to protein-ligand interactions.
    Li GB; Yang LL; Wang WJ; Li LL; Yang SY
    J Chem Inf Model; 2013 Mar; 53(3):592-600. PubMed ID: 23394072
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Data Mining Meets Machine Learning: A Novel ANN-based Multi-body Interaction Docking Scoring Function (MBI-score) Based on Utilizing Frequent Geometric and Chemical Patterns of Interfacial Atoms in Native Protein-ligand Complexes.
    Khashan R; Tropsha A; Zheng W
    Mol Inform; 2022 Aug; 41(8):e2100248. PubMed ID: 35142086
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Beware of machine learning-based scoring functions-on the danger of developing black boxes.
    Gabel J; Desaphy J; Rognan D
    J Chem Inf Model; 2014 Oct; 54(10):2807-15. PubMed ID: 25207678
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Task-Specific Scoring Functions for Predicting Ligand Binding Poses and Affinity and for Screening Enrichment.
    Ashtawy HM; Mahapatra NR
    J Chem Inf Model; 2018 Jan; 58(1):119-133. PubMed ID: 29190087
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.