A unified deep-learning network to accurately segment insulin granules of different animal models im

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Xiaoya Zhang1,
Xiaohong Peng1,4,
Chengsheng Han1,
Wenzhen Zhu1,
Lisi Wei1,
Yulin Zhang1,
Yi Wang1,
Xiuqin Zhang1,
Hao Tang3,
Jianshe Zhang5,
Xiaojun Xu2,
Fengping Feng2,5,
Yanhong Xue2,,
Erlin Yao3,,
Guangming Tan3,
Tao Xu2,3,
Liangyi Chen1
1 State Key Laboratory of Membrane Biology, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine, Peking University, Beijing 100871, China;
2 National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China;
3 University of Chinese Academy of Sciences, Beijing 100049, China;
4 Drug Discovery Center, Key Laboratory of Chemical Genomics, Peking University Shenzhen Graduate School, Shenzhen 518055, China;
5 Marine Science College of Zhejiang Ocean University, National Engineering Research Center of Marine Facilities Aquaculture, Zhoushan 316022, China
Funds: This work was supported by grants from the National Key R&D Program of China (Grant Nos. 2017YFA0504700 and 2016YFA0500400), the National Natural Science Foundation of China (Grant Nos. 31570839, 31661143041, 61472395, 31327901, 31521062 and 31730054), the Beijing Natural Science Foundation (L172003) and Joint Program between Chinese Academy of Sciences and Peking University.

Abstract

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http://www.protein-cell.org/article/exportPdf?id=90a1588a-d815-45a6-b8d7-08f36e446053&language=en

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