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 *

127 related articles for article (PubMed ID: 34342466)

  • 1.
    Marques G; Leswing K; Robertson T; Giesen D; Halls MD; Goldberg A; Marshall K; Staker J; Morisato T; Maeshima H; Arai H; Sasago M; Fujii E; Matsuzawa NN
    J Phys Chem A; 2021 Aug; 125(33):7331-7343. PubMed ID: 34342466
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Massive Theoretical Screen of Hole Conducting Organic Materials in the Heteroacene Family by Using a Cloud-Computing Environment.
    Matsuzawa NN; Arai H; Sasago M; Fujii E; Goldberg A; Mustard TJ; Kwak HS; Giesen DJ; Ranalli F; Halls MD
    J Phys Chem A; 2020 Mar; 124(10):1981-1992. PubMed ID: 32069044
    [TBL] [Abstract][Full Text] [Related]  

  • 3.
    Staker J; Marshall K; Leswing K; Robertson T; Halls MD; Goldberg A; Morisato T; Maeshima H; Ando T; Arai H; Sasago M; Fujii E; Matsuzawa NN
    J Phys Chem A; 2022 Sep; 126(34):5837-5852. PubMed ID: 35984470
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Design of Molecules with Low Hole and Electron Reorganization Energy Using DFT Calculations and Bayesian Optimization.
    Ando T; Shimizu N; Yamamoto N; Matsuzawa NN; Maeshima H; Kaneko H
    J Phys Chem A; 2022 Sep; 126(36):6336-6347. PubMed ID: 36053017
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Machine-Learning Guided Quantum Chemical and Molecular Dynamics Calculations to Design Novel Hole-Conducting Organic Materials.
    Antono E; Matsuzawa NN; Ling J; Saal JE; Arai H; Sasago M; Fujii E
    J Phys Chem A; 2020 Oct; 124(40):8330-8340. PubMed ID: 32940470
    [TBL] [Abstract][Full Text] [Related]  

  • 6. De Novo Direct Inverse QSPR/QSAR: Chemical Variational Autoencoder and Gaussian Mixture Regression Models.
    Nemoto K; Kaneko H
    J Chem Inf Model; 2023 Feb; 63(3):794-805. PubMed ID: 36635071
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Generative Adversarial Networks for De Novo Molecular Design.
    Lee YJ; Kahng H; Kim SB
    Mol Inform; 2021 Oct; 40(10):e2100045. PubMed ID: 34622551
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Adversarial Threshold Neural Computer for Molecular de Novo Design.
    Putin E; Asadulaev A; Vanhaelen Q; Ivanenkov Y; Aladinskaya AV; Aliper A; Zhavoronkov A
    Mol Pharm; 2018 Oct; 15(10):4386-4397. PubMed ID: 29569445
    [TBL] [Abstract][Full Text] [Related]  

  • 9. SMILES-based deep generative scaffold decorator for de-novo drug design.
    Arús-Pous J; Patronov A; Bjerrum EJ; Tyrchan C; Reymond JL; Chen H; Engkvist O
    J Cheminform; 2020 May; 12(1):38. PubMed ID: 33431013
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Shape-Based Generative Modeling for de Novo Drug Design.
    Skalic M; Jiménez J; Sabbadin D; De Fabritiis G
    J Chem Inf Model; 2019 Mar; 59(3):1205-1214. PubMed ID: 30762364
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Design of New Inorganic Crystals with the Desired Composition Using Deep Learning.
    Han S; Lee J; Han S; Moosavi SM; Kim J; Park C
    J Chem Inf Model; 2023 Sep; 63(18):5755-5763. PubMed ID: 37683188
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Geometry-Based Molecular Generation With Deep Constrained Variational Autoencoder.
    Li C; Yao J; Wei W; Niu Z; Zeng X; Li J; Wang J
    IEEE Trans Neural Netw Learn Syst; 2024 Apr; 35(4):4852-4861. PubMed ID: 35171779
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Molecular Property Prediction and Molecular Design Using a Supervised Grammar Variational Autoencoder.
    Oliveira AF; Da Silva JLF; Quiles MG
    J Chem Inf Model; 2022 Feb; 62(4):817-828. PubMed ID: 35174705
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Molecular generative model based on conditional variational autoencoder for de novo molecular design.
    Lim J; Ryu S; Kim JW; Kim WY
    J Cheminform; 2018 Jul; 10(1):31. PubMed ID: 29995272
    [TBL] [Abstract][Full Text] [Related]  

  • 15. The theoretical investigation on the 4-(4-phenyl-4-α-naphthylbutadieny)-triphenylamine derivatives as hole transporting materials for perovskite-type solar cells.
    Chi WJ; Li ZS
    Phys Chem Chem Phys; 2015 Feb; 17(8):5991-8. PubMed ID: 25642469
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Theoretical insights into the 1D-charge transport properties in a series of hexaazatrinaphthylene-based discotic molecules.
    An B; Wen K; Feng S; Pan X; Wu W; Guo X; Zhang J
    J Comput Chem; 2018 May; 39(13):773-779. PubMed ID: 29280163
    [TBL] [Abstract][Full Text] [Related]  

  • 17. De Novo Molecule Design by Translating from Reduced Graphs to SMILES.
    Pogány P; Arad N; Genway S; Pickett SD
    J Chem Inf Model; 2019 Mar; 59(3):1136-1146. PubMed ID: 30525594
    [TBL] [Abstract][Full Text] [Related]  

  • 18. UnCorrupt SMILES: a novel approach to de novo design.
    Schoenmaker L; Béquignon OJM; Jespers W; van Westen GJP
    J Cheminform; 2023 Feb; 15(1):22. PubMed ID: 36788579
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Deep reinforcement learning for de novo drug design.
    Popova M; Isayev O; Tropsha A
    Sci Adv; 2018 Jul; 4(7):eaap7885. PubMed ID: 30050984
    [TBL] [Abstract][Full Text] [Related]  

  • 20. MGCVAE: Multi-Objective Inverse Design via Molecular Graph Conditional Variational Autoencoder.
    Lee M; Min K
    J Chem Inf Model; 2022 Jun; 62(12):2943-2950. PubMed ID: 35666276
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.