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Journal Abstract Search

454 related items for PubMed ID: 30698019

  • 1. Deep learning for molecular generation.
    Xu Y, Lin K, Wang S, Wang L, Cai C, Song C, Lai L, Pei J.
    Future Med Chem; 2019 Mar; 11(6):567-597. PubMed ID: 30698019
    [Abstract] [Full Text] [Related]

  • 2. Generative Deep Learning for Targeted Compound Design.
    Sousa T, Correia J, Pereira V, Rocha M.
    J Chem Inf Model; 2021 Nov 22; 61(11):5343-5361. PubMed ID: 34699719
    [Abstract] [Full Text] [Related]

  • 3. Graph-based generative models for de Novo drug design.
    Xia X, Hu J, Wang Y, Zhang L, Liu Z.
    Drug Discov Today Technol; 2019 Dec 22; 32-33():45-53. PubMed ID: 33386094
    [Abstract] [Full Text] [Related]

  • 4. Deep learning approaches for de novo drug design: An overview.
    Wang M, Wang Z, Sun H, Wang J, Shen C, Weng G, Chai X, Li H, Cao D, Hou T.
    Curr Opin Struct Biol; 2022 Feb 22; 72():135-144. PubMed ID: 34823138
    [Abstract] [Full Text] [Related]

  • 5. The power of deep learning to ligand-based novel drug discovery.
    Baskin II.
    Expert Opin Drug Discov; 2020 Jul 22; 15(7):755-764. PubMed ID: 32228116
    [Abstract] [Full Text] [Related]

  • 6. Deep Learning Applied to Ligand-Based De Novo Drug Design.
    Palazzesi F, Pozzan A.
    Methods Mol Biol; 2022 Jul 22; 2390():273-299. PubMed ID: 34731474
    [Abstract] [Full Text] [Related]

  • 7. Training recurrent neural networks as generative neural networks for molecular structures: how does it impact drug discovery?
    D'Souza S, Kv P, Balaji S.
    Expert Opin Drug Discov; 2022 Oct 22; 17(10):1071-1079. PubMed ID: 36216812
    [Abstract] [Full Text] [Related]

  • 8. Generative chemistry: drug discovery with deep learning generative models.
    Bian Y, Xie XQ.
    J Mol Model; 2021 Feb 04; 27(3):71. PubMed ID: 33543405
    [Abstract] [Full Text] [Related]

  • 9. Molecular design in drug discovery: a comprehensive review of deep generative models.
    Cheng Y, Gong Y, Liu Y, Song B, Zou Q.
    Brief Bioinform; 2021 Nov 05; 22(6):. PubMed ID: 34415297
    [Abstract] [Full Text] [Related]

  • 10. Advances and Challenges in De Novo Drug Design Using Three-Dimensional Deep Generative Models.
    Xie W, Wang F, Li Y, Lai L, Pei J.
    J Chem Inf Model; 2022 May 23; 62(10):2269-2279. PubMed ID: 35544331
    [Abstract] [Full Text] [Related]

  • 11. Comprehensive assessment of deep generative architectures for de novo drug design.
    Wang M, Sun H, Wang J, Pang J, Chai X, Xu L, Li H, Cao D, Hou T.
    Brief Bioinform; 2022 Jan 17; 23(1):. PubMed ID: 34929743
    [Abstract] [Full Text] [Related]

  • 12. Recent Progress of Deep Learning in Drug Discovery.
    Wang F, Diao X, Chang S, Xu L.
    Curr Pharm Des; 2021 Jan 17; 27(17):2088-2096. PubMed ID: 33511933
    [Abstract] [Full Text] [Related]

  • 13. Deep Reinforcement Learning for Multiparameter Optimization in de novo Drug Design.
    Ståhl N, Falkman G, Karlsson A, Mathiason G, Boström J.
    J Chem Inf Model; 2019 Jul 22; 59(7):3166-3176. PubMed ID: 31273995
    [Abstract] [Full Text] [Related]

  • 14. Relevant Applications of Generative Adversarial Networks in Drug Design and Discovery: Molecular De Novo Design, Dimensionality Reduction, and De Novo Peptide and Protein Design.
    Lin E, Lin CH, Lane HY.
    Molecules; 2020 Jul 16; 25(14):. PubMed ID: 32708785
    [Abstract] [Full Text] [Related]

  • 15. De Novo Peptide and Protein Design Using Generative Adversarial Networks: An Update.
    Lin E, Lin CH, Lane HY.
    J Chem Inf Model; 2022 Feb 28; 62(4):761-774. PubMed ID: 35128926
    [Abstract] [Full Text] [Related]

  • 16. Reinforced Adversarial Neural Computer for de Novo Molecular Design.
    Putin E, Asadulaev A, Ivanenkov Y, Aladinskiy V, Sanchez-Lengeling B, Aspuru-Guzik A, Zhavoronkov A.
    J Chem Inf Model; 2018 Jun 25; 58(6):1194-1204. PubMed ID: 29762023
    [Abstract] [Full Text] [Related]

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  • 19. Navigating the frontier of drug-like chemical space with cutting-edge generative AI models.
    Lavecchia A.
    Drug Discov Today; 2024 Sep 25; 29(9):104133. PubMed ID: 39103144
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