التفاصيل البيبلوغرافية
| العنوان: |
Deep learning based local feature classification to automatically identify single molecule fluorescence events |
| المؤلفون: |
Shuqi Zhou, Yu Miao, Haoren Qiu, Yuan Yao, Wenjuan Wang, Chunlai Chen |
| المصدر: |
Communications Biology, Vol 7, Iss 1, Pp 1-11 (2024) |
| بيانات النشر: |
Nature Portfolio, 2024. |
| سنة النشر: |
2024 |
| المجموعة: |
LCC:Biology (General) |
| مصطلحات موضوعية: |
Biology (General), QH301-705.5 |
| الوصف: |
Abstract Long-term single-molecule fluorescence measurements are widely used powerful tools to study the conformational dynamics of biomolecules in real time to further elucidate their conformational dynamics. Typically, thousands or even more single-molecule traces are analyzed to provide statistically meaningful information, which is labor-intensive and can introduce user bias. Recently, several deep-learning models have been developed to automatically classify single-molecule traces. In this study, we introduce DEBRIS (Deep lEarning Based fRagmentatIon approach for Single-molecule fluorescence event identification), a deep-learning model focusing on classifying local features and capable of automatically identifying steady fluorescence signals and dynamically emerging signals of different patterns. DEBRIS efficiently and accurately identifies both one-color and two-color single-molecule events, including their start and end points. By adjusting user-defined criteria, DEBRIS becomes the pioneer in using a deep learning model to accurately classify four different types of single-molecule fluorescence events using the same trained model, demonstrating its universality and ability to enrich the current toolbox. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
2399-3642 |
| Relation: |
https://doaj.org/toc/2399-3642 |
| DOI: |
10.1038/s42003-024-07122-4 |
| URL الوصول: |
https://doaj.org/article/8c656b99862742c8b42dfa324e1108a1 |
| رقم الانضمام: |
edsdoj.8c656b99862742c8b42dfa324e1108a1 |
| قاعدة البيانات: |
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