| Autor: |
Liqing Liu, Hongjun Wu, Shuxin Yang, Ke Yi, Junjie Hu, Li Xiao, Tao Xu |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
STAR Protocols, Vol 4, Iss 4, Pp 102558- (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2666-1667 |
| DOI: |
10.1016/j.xpro.2023.102558 |
| Popis: |
Summary: DeepContact is a deep learning software for high-throughput quantification of membrane contact site (MCS) in 2D electron microscopy images. This protocol will guide users through incorporating available DeepContact models in Amira’s artificial intelligence module, thereby allowing invoking of DeepContact functions in organelle segmentation and quantifying of MCS with a user-friendly graphical user interface of Amira software.For complete details on the use and execution of this protocol, please refer to Liu et al. (2022).1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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