BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

283 related articles for article (PubMed ID: 32282202)

  • 1. LIT-PCBA: An Unbiased Data Set for Machine Learning and Virtual Screening.
    Tran-Nguyen VK; Jacquemard C; Rognan D
    J Chem Inf Model; 2020 Sep; 60(9):4263-4273. PubMed ID: 32282202
    [TBL] [Abstract][Full Text] [Related]  

  • 2. TocoDecoy: A New Approach to Design Unbiased Datasets for Training and Benchmarking Machine-Learning Scoring Functions.
    Zhang X; Shen C; Liao B; Jiang D; Wang J; Wu Z; Du H; Wang T; Huo W; Xu L; Cao D; Hsieh CY; Hou T
    J Med Chem; 2022 Jun; 65(11):7918-7932. PubMed ID: 35642777
    [TBL] [Abstract][Full Text] [Related]  

  • 3. MILCDock: Machine Learning Enhanced Consensus Docking for Virtual Screening in Drug Discovery.
    Morris CJ; Stern JA; Stark B; Christopherson M; Della Corte D
    J Chem Inf Model; 2022 Nov; 62(22):5342-5350. PubMed ID: 36342217
    [TBL] [Abstract][Full Text] [Related]  

  • 4. FRAGSITE: A Fragment-Based Approach for Virtual Ligand Screening.
    Zhou H; Cao H; Skolnick J
    J Chem Inf Model; 2021 Apr; 61(4):2074-2089. PubMed ID: 33724022
    [TBL] [Abstract][Full Text] [Related]  

  • 5. True Accuracy of Fast Scoring Functions to Predict High-Throughput Screening Data from Docking Poses: The Simpler the Better.
    Tran-Nguyen VK; Bret G; Rognan D
    J Chem Inf Model; 2021 Jun; 61(6):2788-2797. PubMed ID: 34109796
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Accuracy or novelty: what can we gain from target-specific machine-learning-based scoring functions in virtual screening?
    Shen C; Weng G; Zhang X; Leung EL; Yao X; Pang J; Chai X; Li D; Wang E; Cao D; Hou T
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33418562
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Toward a benchmarking data set able to evaluate ligand- and structure-based virtual screening using public HTS data.
    Lindh M; Svensson F; Schaal W; Zhang J; Sköld C; Brandt P; Karlén A
    J Chem Inf Model; 2015 Feb; 55(2):343-53. PubMed ID: 25564966
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A comprehensive comparative assessment of 3D molecular similarity tools in ligand-based virtual screening.
    Jiang Z; Xu J; Yan A; Wang L
    Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34151363
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Topology-Based and Conformation-Based Decoys Database: An Unbiased Online Database for Training and Benchmarking Machine-Learning Scoring Functions.
    Zhang X; Shen C; Wang T; Kang Y; Li D; Pan P; Wang J; Wang G; Deng Y; Xu L; Cao D; Hou T; Wang Z
    J Med Chem; 2023 Jul; 66(13):9174-9183. PubMed ID: 37317043
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Validation of a Field-Based Ligand Screener Using a Novel Benchmarking Data Set for Assessing 3D-Based Virtual Screening Methods.
    Giangreco I; Mukhopadhyay A; Cole JC
    J Chem Inf Model; 2021 Dec; 61(12):5841-5852. PubMed ID: 34792345
    [TBL] [Abstract][Full Text] [Related]  

  • 11. An unbiased method to build benchmarking sets for ligand-based virtual screening and its application to GPCRs.
    Xia J; Jin H; Liu Z; Zhang L; Wang XS
    J Chem Inf Model; 2014 May; 54(5):1433-50. PubMed ID: 24749745
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Improved Method of Structure-Based Virtual Screening via Interaction-Energy-Based Learning.
    Yasuo N; Sekijima M
    J Chem Inf Model; 2019 Mar; 59(3):1050-1061. PubMed ID: 30808172
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Protein-Ligand Docking in the Machine-Learning Era.
    Yang C; Chen EA; Zhang Y
    Molecules; 2022 Jul; 27(14):. PubMed ID: 35889440
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. Benchmarking Data Sets from PubChem BioAssay Data: Current Scenario and Room for Improvement.
    Tran-Nguyen VK; Rognan D
    Int J Mol Sci; 2020 Jun; 21(12):. PubMed ID: 32575564
    [TBL] [Abstract][Full Text] [Related]  

  • 16. GPCR-Bench: A Benchmarking Set and Practitioners' Guide for G Protein-Coupled Receptor Docking.
    Weiss DR; Bortolato A; Tehan B; Mason JS
    J Chem Inf Model; 2016 Apr; 56(4):642-51. PubMed ID: 26958710
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Virtual Screening with Gnina 1.0.
    Sunseri J; Koes DR
    Molecules; 2021 Dec; 26(23):. PubMed ID: 34885952
    [TBL] [Abstract][Full Text] [Related]  

  • 18. The Development of Target-Specific Pose Filter Ensembles To Boost Ligand Enrichment for Structure-Based Virtual Screening.
    Xia J; Hsieh JH; Hu H; Wu S; Wang XS
    J Chem Inf Model; 2017 Jun; 57(6):1414-1425. PubMed ID: 28511009
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Comparison of ligand- and structure-based virtual screening on the DUD data set.
    von Korff M; Freyss J; Sander T
    J Chem Inf Model; 2009 Feb; 49(2):209-31. PubMed ID: 19434824
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 15.