Deep learning-based investigation of chloroplast translation regulatory sequences
Understanding the architecture of translational regulatory sequences in diverse chloroplasts is critical for advancing synthetic biology and genetic engineering. In this study, a hybrid deep learning model combining convolutional neural network (CNN), long short-term memory (LSTM), Attention, and Re...
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| Автори: | , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
Frontiers Media S.A.
2025-12-01
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| Серія: | Frontiers in Plant Science |
| Предмети: | |
| Онлайн доступ: | https://www.frontiersin.org/articles/10.3389/fpls.2025.1698951/full |
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