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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/54408
Title: Application of semi-supervised GAN in combination with JT-VAE for generation of small molecules with high binding affinity to the KasA enzyme of Mycobacterium tuberculosis
Authors: Gonchar, A. V.
Tuzikov, A. V.
Fur, K. V.
Andrianov, A. M.
Keywords: материалы конференций;mycobacterium tuberculosis (Mtb);generative adversarial neural network (GAN);virtual screening
Issue Date: 2023
Publisher: BSU
Citation: Application of semi-supervised GAN in combination with JT-VAE for generation of small molecules with high binding affinity to the KasA enzyme of Mycobacterium tuberculosis / A. V. Gonchar [et al.] // Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023) : Proceedings of the 16th International Conference, October 17–19, 2023, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2023. – P. 114–117.
Abstract: Semi-supervised generative adversarial neural network trained on molecular graph embeddings produced by Junction Tree Variational Autoencoder was implemented and applied for de novo design of new potential inhibitors of Mycobacterium tuberculosis protein KasA.
URI: https://libeldoc.bsuir.by/handle/123456789/54408
Appears in Collections:Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023)

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