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An interactive deep learning-based approach reveals mitochondrial cristae topologies
Shogo Suga, Koki Nakamura, Bruno M. Humbel, Hiroki Kawai, View ORCID ProfileYusuke Hirabayashi
doi: https://doi.org/10.1101/2021.06.11.448083
Shogo Suga
1Department of Chemistry and Biotechnology, School of Engineering - The University of Tokyo
Koki Nakamura
1Department of Chemistry and Biotechnology, School of Engineering - The University of Tokyo
Bruno M. Humbel
2Imaging Section, Okinawa Institute of Science and Technology (OIST), Okinawa
904-0495, Japan
3Department of Cell Biology and Neuroscience, Juntendo University Graduate School of Medicine, Tokyo 113-8421, Japan
Hiroki Kawai
1Department of Chemistry and Biotechnology, School of Engineering - The University of Tokyo
Yusuke Hirabayashi
1Department of Chemistry and Biotechnology, School of Engineering - The University of Tokyo
Posted June 11, 2021.
An interactive deep learning-based approach reveals mitochondrial cristae topologies
Shogo Suga, Koki Nakamura, Bruno M. Humbel, Hiroki Kawai, Yusuke Hirabayashi
bioRxiv 2021.06.11.448083; doi: https://doi.org/10.1101/2021.06.11.448083
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