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https://elib.bsu.by/handle/123456789/306211Полная запись метаданных
| Поле DC | Значение | Язык |
|---|---|---|
| dc.contributor.author | Gonchar, Anna V. | |
| dc.contributor.author | Tuzikov, Alexander V. | |
| dc.contributor.author | Furs, Konstantin V. | |
| dc.contributor.author | Andrianov, Alexander M. | |
| dc.date.accessioned | 2023-12-12T12:42:11Z | - |
| dc.date.available | 2023-12-12T12:42:11Z | - |
| dc.date.issued | 2023 | |
| dc.identifier.citation | Pattern Recognition and Information Processing (PRIP’2023). Artificial Universe: New Horisont : Proceedings of the 16 th International Conference, Belarus, Minsk, October 17–19, 2023 / Belarusian State University : eds. A. Nedzved, A. Belotserkovsky. – Minsk : BSU, 2023. – Pp. 114-117. | |
| dc.identifier.isbn | 978-985-881-522-6 | |
| dc.identifier.uri | https://elib.bsu.by/handle/123456789/306211 | - |
| dc.description.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 | |
| dc.description.sponsorship | This work was supported by grants from the Belarusian Republican Foundation for Fundamental Research (F23-007) and the Consortium and the Drug Resistant Tuberculosis Portal Program (https://tbportals.niaid.nih.gov). | |
| dc.language.iso | en | |
| dc.publisher | Minsk : BSU | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.subject | ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Кибернетика | |
| dc.subject | ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика | |
| dc.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 | |
| dc.type | conference paper | |
| Располагается в коллекциях: | 2023. Pattern Recognition and Information Processing (PRIP’2023). Artificial Intelliverse: Expanding Horizons | |
Полный текст документа:
| Файл | Описание | Размер | Формат | |
|---|---|---|---|---|
| 114-117.pdf | 368,83 kB | Adobe PDF | Открыть |
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