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 *

126 related articles for article (PubMed ID: 32639154)

  • 21. 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]  

  • 22. A benchmark testing ground for integrating homology modeling and protein docking.
    Bohnuud T; Luo L; Wodak SJ; Bonvin AM; Weng Z; Vajda S; Schueler-Furman O; Kozakov D
    Proteins; 2017 Jan; 85(1):10-16. PubMed ID: 27172383
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Comparative modeling and benchmarking data sets for human histone deacetylases and sirtuin families.
    Xia J; Tilahun EL; Kebede EH; Reid TE; Zhang L; Wang XS
    J Chem Inf Model; 2015 Feb; 55(2):374-88. PubMed ID: 25633490
    [TBL] [Abstract][Full Text] [Related]  

  • 24. NeuroPycon: An open-source python toolbox for fast multi-modal and reproducible brain connectivity pipelines.
    Meunier D; Pascarella A; Altukhov D; Jas M; Combrisson E; Lajnef T; Bertrand-Dubois D; Hadid V; Alamian G; Alves J; Barlaam F; Saive AL; Dehgan A; Jerbi K
    Neuroimage; 2020 Oct; 219():117020. PubMed ID: 32522662
    [TBL] [Abstract][Full Text] [Related]  

  • 25. 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]  

  • 26. DynBench3D, a Web-Resource to Dynamically Generate Benchmark Sets of Large Heteromeric Protein Complexes.
    Bertoni M; Aloy P
    J Mol Biol; 2018 Oct; 430(21):4431-4438. PubMed ID: 30274705
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Evaluation and optimization of virtual screening workflows with DEKOIS 2.0--a public library of challenging docking benchmark sets.
    Bauer MR; Ibrahim TM; Vogel SM; Boeckler FM
    J Chem Inf Model; 2013 Jun; 53(6):1447-62. PubMed ID: 23705874
    [TBL] [Abstract][Full Text] [Related]  

  • 28. A graph-based approach to construct target-focused libraries for virtual screening.
    Naderi M; Alvin C; Ding Y; Mukhopadhyay S; Brylinski M
    J Cheminform; 2016; 8():14. PubMed ID: 26981157
    [TBL] [Abstract][Full Text] [Related]  

  • 29. OpenBioLink: a benchmarking framework for large-scale biomedical link prediction.
    Breit A; Ott S; Agibetov A; Samwald M
    Bioinformatics; 2020 Jul; 36(13):4097-4098. PubMed ID: 32339214
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Ringtail: A Python Tool for Efficient Management and Storage of Virtual Screening Results.
    Hansel-Harris AT; Santos-Martins D; Bruciaferri N; Tillack AF; Holcomb M; Forli S
    J Chem Inf Model; 2023 Apr; 63(7):1858-1864. PubMed ID: 36976961
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Benchmarking of HPCC: A novel 3D molecular representation combining shape and pharmacophoric descriptors for efficient molecular similarity assessments.
    Karaboga AS; Petronin F; Marchetti G; Souchet M; Maigret B
    J Mol Graph Model; 2013 Apr; 41():20-30. PubMed ID: 23467019
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models.
    Polykovskiy D; Zhebrak A; Sanchez-Lengeling B; Golovanov S; Tatanov O; Belyaev S; Kurbanov R; Artamonov A; Aladinskiy V; Veselov M; Kadurin A; Johansson S; Chen H; Nikolenko S; Aspuru-Guzik A; Zhavoronkov A
    Front Pharmacol; 2020; 11():565644. PubMed ID: 33390943
    [TBL] [Abstract][Full Text] [Related]  

  • 33. poreTally: run and publish de novo nanopore assembler benchmarks.
    de Lannoy C; Risse J; de Ridder D
    Bioinformatics; 2019 Aug; 35(15):2663-2664. PubMed ID: 30590415
    [TBL] [Abstract][Full Text] [Related]  

  • 34. immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking.
    Weber CR; Akbar R; Yermanos A; Pavlović M; Snapkov I; Sandve GK; Reddy ST; Greiff V
    Bioinformatics; 2020 Jun; 36(11):3594-3596. PubMed ID: 32154832
    [TBL] [Abstract][Full Text] [Related]  

  • 35. FINDSITE
    Zhou H; Cao H; Skolnick J
    J Chem Inf Model; 2018 Nov; 58(11):2343-2354. PubMed ID: 30278128
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Nestly--a framework for running software with nested parameter choices and aggregating results.
    McCoy CO; Gallagher A; Hoffman NG; Matsen FA
    Bioinformatics; 2013 Feb; 29(3):387-8. PubMed ID: 23220574
    [TBL] [Abstract][Full Text] [Related]  

  • 37. 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]  

  • 38. Benchmark of four popular virtual screening programs: construction of the active/decoy dataset remains a major determinant of measured performance.
    Chaput L; Martinez-Sanz J; Saettel N; Mouawad L
    J Cheminform; 2016; 8():56. PubMed ID: 27803745
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Cross-docking benchmark for automated pose and ranking prediction of ligand binding.
    Wierbowski SD; Wingert BM; Zheng J; Camacho CJ
    Protein Sci; 2020 Jan; 29(1):298-305. PubMed ID: 31721338
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Importance of the pharmacological profile of the bound ligand in enrichment on nuclear receptors: toward the use of experimentally validated decoy ligands.
    Lagarde N; Zagury JF; Montes M
    J Chem Inf Model; 2014 Oct; 54(10):2915-44. PubMed ID: 25250508
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 7.