CryoDRGN: Reconstruction of heterogeneous structures from cryo-electron micrographs using neural networks

Ellen D. Zhong; Tristan Bepler; Bonnie Berger; Joseph H. Davis

doi:10.1101/2020.03.27.003871

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CryoDRGN: Reconstruction of heterogeneous structures from cryo-electron micrographs using neural networks

View ORCID ProfileEllen D. Zhong, View ORCID ProfileTristan Bepler, Bonnie Berger, View ORCID ProfileJoseph H. Davis

doi: https://doi.org/10.1101/2020.03.27.003871

Ellen D. Zhong

1Computational and Systems Biology, Massachusetts Institute of Technology, Cambridge, MA 02139

2Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139

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ORCID record for Ellen D. Zhong

Tristan Bepler

1Computational and Systems Biology, Massachusetts Institute of Technology, Cambridge, MA 02139

2Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139

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ORCID record for Tristan Bepler

Bonnie Berger

2Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139

3Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139

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For correspondence: [email protected] [email protected]

Joseph H. Davis

1Computational and Systems Biology, Massachusetts Institute of Technology, Cambridge, MA 02139

4Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139

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ORCID record for Joseph H. Davis
For correspondence: [email protected] [email protected]

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Posted March 29, 2020.

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CryoDRGN: Reconstruction of heterogeneous structures from cryo-electron micrographs using neural networks

Ellen D. Zhong, Tristan Bepler, Bonnie Berger, Joseph H. Davis

bioRxiv 2020.03.27.003871; doi: https://doi.org/10.1101/2020.03.27.003871

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CryoDRGN: Reconstruction of heterogeneous structures from cryo-electron micrographs using neural networks

Ellen D. Zhong, Tristan Bepler, Bonnie Berger, Joseph H. Davis

bioRxiv 2020.03.27.003871; doi: https://doi.org/10.1101/2020.03.27.003871

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