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171 related items for PubMed ID: 33430996

  • 1. Multiobjective de novo drug design with recurrent neural networks and nondominated sorting.
    Yasonik J.
    J Cheminform; 2020 Feb 18; 12(1):14. PubMed ID: 33430996
    [Abstract] [Full Text] [Related]

  • 2. De novo drug design based on Stack-RNN with multi-objective reward-weighted sum and reinforcement learning.
    Hu P, Zou J, Yu J, Shi S.
    J Mol Model; 2023 Mar 30; 29(4):121. PubMed ID: 36991180
    [Abstract] [Full Text] [Related]

  • 3. De Novo Drug Design of Targeted Chemical Libraries Based on Artificial Intelligence and Pair-Based Multiobjective Optimization.
    Domenico A, Nicola G, Daniela T, Fulvio C, Nicola A, Orazio N.
    J Chem Inf Model; 2020 Oct 26; 60(10):4582-4593. PubMed ID: 32845150
    [Abstract] [Full Text] [Related]

  • 4. De novo drug design by iterative multiobjective deep reinforcement learning with graph-based molecular quality assessment.
    Fang Y, Pan X, Shen HB.
    Bioinformatics; 2023 Apr 03; 39(4):. PubMed ID: 36961341
    [Abstract] [Full Text] [Related]

  • 5. De novo drug design using multiobjective evolutionary graphs.
    Nicolaou CA, Apostolakis J, Pattichis CS.
    J Chem Inf Model; 2009 Feb 03; 49(2):295-307. PubMed ID: 19434831
    [Abstract] [Full Text] [Related]

  • 6. Development of scoring-assisted generative exploration (SAGE) and its application to dual inhibitor design for acetylcholinesterase and monoamine oxidase B.
    Lim H.
    J Cheminform; 2024 May 24; 16(1):59. PubMed ID: 38790018
    [Abstract] [Full Text] [Related]

  • 7. Designing optimized drug candidates with Generative Adversarial Network.
    Abbasi M, Santos BP, Pereira TC, Sofia R, Monteiro NRC, Simões CJV, Brito RMM, Ribeiro B, Oliveira JL, Arrais JP.
    J Cheminform; 2022 Jun 26; 14(1):40. PubMed ID: 35754029
    [Abstract] [Full Text] [Related]

  • 8. Status and Prospects of Research on Deep Learning-based De Novo Generation of Drug Molecules.
    Shi H, Wang Z, Zhou L, Xu Z, Xie L, Kong R, Chang S.
    Curr Comput Aided Drug Des; 2024 Feb 06. PubMed ID: 38321907
    [Abstract] [Full Text] [Related]

  • 9. De novo design of potential RecA inhibitors using multi objective optimization.
    Sengupta S, Bandyopadhyay S.
    IEEE/ACM Trans Comput Biol Bioinform; 2012 Feb 06; 9(4):1139-54. PubMed ID: 22392725
    [Abstract] [Full Text] [Related]

  • 10. Optimizing blood-brain barrier permeation through deep reinforcement learning for de novo drug design.
    Pereira T, Abbasi M, Oliveira JL, Ribeiro B, Arrais J.
    Bioinformatics; 2021 Jul 12; 37(Suppl_1):i84-i92. PubMed ID: 34252946
    [Abstract] [Full Text] [Related]

  • 11. Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks.
    Segler MHS, Kogej T, Tyrchan C, Waller MP.
    ACS Cent Sci; 2018 Jan 24; 4(1):120-131. PubMed ID: 29392184
    [Abstract] [Full Text] [Related]

  • 12. Mothra: Multiobjective de novo Molecular Generation Using Monte Carlo Tree Search.
    Suzuki T, Ma D, Yasuo N, Sekijima M.
    J Chem Inf Model; 2024 Oct 14; 64(19):7291-7302. PubMed ID: 39317969
    [Abstract] [Full Text] [Related]

  • 13. ChemTS: an efficient python library for de novo molecular generation.
    Yang X, Zhang J, Yoshizoe K, Terayama K, Tsuda K.
    Sci Technol Adv Mater; 2017 Oct 14; 18(1):972-976. PubMed ID: 29435094
    [Abstract] [Full Text] [Related]

  • 14. Guidelines for Recurrent Neural Network Transfer Learning-Based Molecular Generation of Focused Libraries.
    Amabilino S, Pogány P, Pickett SD, Green DVS.
    J Chem Inf Model; 2020 Dec 28; 60(12):5699-5713. PubMed ID: 32659085
    [Abstract] [Full Text] [Related]

  • 15. Augmented Hill-Climb increases reinforcement learning efficiency for language-based de novo molecule generation.
    Thomas M, O'Boyle NM, Bender A, de Graaf C.
    J Cheminform; 2022 Oct 03; 14(1):68. PubMed ID: 36192789
    [Abstract] [Full Text] [Related]

  • 16. GuacaMol: Benchmarking Models for de Novo Molecular Design.
    Brown N, Fiscato M, Segler MHS, Vaucher AC.
    J Chem Inf Model; 2019 Mar 25; 59(3):1096-1108. PubMed ID: 30887799
    [Abstract] [Full Text] [Related]

  • 17. Generative and reinforcement learning approaches for the automated de novo design of bioactive compounds.
    Korshunova M, Huang N, Capuzzi S, Radchenko DS, Savych O, Moroz YS, Wells CI, Willson TM, Tropsha A, Isayev O.
    Commun Chem; 2022 Oct 18; 5(1):129. PubMed ID: 36697952
    [Abstract] [Full Text] [Related]

  • 18. GENERA: A Combined Genetic/Deep-Learning Algorithm for Multiobjective Target-Oriented De Novo Design.
    Lamanna G, Delre P, Marcou G, Saviano M, Varnek A, Horvath D, Mangiatordi GF.
    J Chem Inf Model; 2023 Aug 28; 63(16):5107-5119. PubMed ID: 37556857
    [Abstract] [Full Text] [Related]

  • 19. 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 28; 11(6):567-597. PubMed ID: 30698019
    [Abstract] [Full Text] [Related]

  • 20. 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 01; 15(10):4386-4397. PubMed ID: 29569445
    [Abstract] [Full Text] [Related]

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