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 *

123 related articles for article (PubMed ID: 37824704)

  • 1. Cluster-MLP: An Active Learning Genetic Algorithm Framework for Accelerated Discovery of Global Minimum Configurations of Pure and Alloyed Nanoclusters.
    Raju RK; Sivakumar S; Wang X; Ulissi ZW
    J Chem Inf Model; 2023 Oct; 63(20):6192-6197. PubMed ID: 37824704
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Combining Deep Learning Neural Networks with Genetic Algorithms to Map Nanocluster Configuration Spaces with Quantum Accuracy at Low Computational Cost.
    von der Heyde J; Malone W; Zaman N; Kara A
    J Chem Inf Model; 2023 Aug; 63(16):5045-5055. PubMed ID: 37579032
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Modeling microsolvation clusters with electronic-structure calculations guided by analytical potentials and predictive machine learning techniques.
    Jesus WS; Prudente FV; Marques JMC; Pereira FB
    Phys Chem Chem Phys; 2021 Jan; 23(2):1738-1749. PubMed ID: 33427847
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Self-Consistent Charge Density-Functional Tight-Binding Parametrization for Pt-Ru Alloys.
    Shi H; Koskinen P; Ramasubramaniam A
    J Phys Chem A; 2017 Mar; 121(12):2497-2502. PubMed ID: 28267337
    [TBL] [Abstract][Full Text] [Related]  

  • 5. An approach based on genetic algorithms and machine learning coupled for studying alloy and molecular clusters by optimizing quantum energy surfaces.
    Rezende UL; De Souza LA; Belchior JC
    J Comput Chem; 2023 Sep; 44(24):1956-1969. PubMed ID: 37306361
    [TBL] [Abstract][Full Text] [Related]  

  • 6. "Teamwork Makes the Dream Work": Tribal Competition Evolutionary Search as a Surrogate for Free-Energy-Based Structural Predictions.
    Loeffler TD; Chan H; Gray S; Sankaranarayanan SKRS
    J Phys Chem A; 2019 May; 123(17):3903-3910. PubMed ID: 30939871
    [TBL] [Abstract][Full Text] [Related]  

  • 7. GAMaterial-A genetic-algorithm software for material design and discovery.
    Lourenço MP; Hostaš J; Herrera LB; Calaminici P; Köster AM; Tchagang A; Salahub DR
    J Comput Chem; 2023 Mar; 44(7):814-823. PubMed ID: 36444916
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Application of Optimization Algorithms in Clusters.
    Srivastava R
    Front Chem; 2021; 9():637286. PubMed ID: 33777900
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Structure prediction of nanoclusters; a direct or a pre-screened search on the DFT energy landscape?
    Farrow MR; Chow Y; Woodley SM
    Phys Chem Chem Phys; 2014 Oct; 16(39):21119-34. PubMed ID: 25017305
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A strategy to find minimal energy nanocluster structures.
    Rogan J; Varas A; Valdivia JA; Kiwi M
    J Comput Chem; 2013 Nov; 34(29):2548-56. PubMed ID: 24037778
    [TBL] [Abstract][Full Text] [Related]  

  • 11. What Electronic Structure Method Can Be Used in the Global Optimization of Nanoclusters?
    Galvão BRL; Viegas LP
    J Phys Chem A; 2019 Dec; 123(48):10454-10462. PubMed ID: 31702154
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Exploration of multiple energy landscapes for zirconia nanoclusters.
    Woodley SM; Hamad S; Catlow CR
    Phys Chem Chem Phys; 2010 Aug; 12(30):8454-65. PubMed ID: 20617256
    [TBL] [Abstract][Full Text] [Related]  

  • 13. MolE8: finding DFT potential energy surface minima values from force-field optimised organic molecules with new machine learning representations.
    Lee S; Ermanis K; Goodman JM
    Chem Sci; 2022 Jun; 13(24):7204-7214. PubMed ID: 35799803
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Unraveling the Planar-Globular Transition in Gold Nanoclusters through Evolutionary Search.
    Kinaci A; Narayanan B; Sen FG; Davis MJ; Gray SK; Sankaranarayanan SK; Chan MK
    Sci Rep; 2016 Nov; 6():34974. PubMed ID: 27892462
    [TBL] [Abstract][Full Text] [Related]  

  • 15. DFT global optimisation of gas-phase and MgO-supported sub-nanometre AuPd clusters.
    Hussein HA; Davis JBA; Johnston RL
    Phys Chem Chem Phys; 2016 Sep; 18(37):26133-26143. PubMed ID: 27711424
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Structural, electronic and vibrational properties of small Ga(x)N(y) (x+y = 2-5) nanoclusters: a B3LYP-DFT study.
    Yadav PS; Yadav RK; Agrawal BK
    J Phys Condens Matter; 2007 Feb; 19(7):076209. PubMed ID: 22251596
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A Global Optimizer for Nanoclusters.
    Khatun M; Majumdar RS; Anoop A
    Front Chem; 2019; 7():644. PubMed ID: 31612127
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Advances in Docking.
    Sulimov VB; Kutov DC; Sulimov AV
    Curr Med Chem; 2019; 26(42):7555-7580. PubMed ID: 30182836
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Alternative search strategy for minimal energy nanocluster structures: the case of rhodium, palladium, and silver.
    Rogan J; García G; Loyola C; Orellana W; Ramírez R; Kiwi M
    J Chem Phys; 2006 Dec; 125(21):214708. PubMed ID: 17166041
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Structure and mobility of metal clusters in MOFs: Au, Pd, and AuPd clusters in MOF-74.
    Vilhelmsen LB; Walton KS; Sholl DS
    J Am Chem Soc; 2012 Aug; 134(30):12807-16. PubMed ID: 22734664
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.