A deep learning approach called DeepPiCt facilitates segmentation and macromolecular identification in the cellular jungle of electron cryotomography data.
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References
Beck, M. & Baumeister, W. Trends Cell Biol. 26, 825–837 (2016).
Wan, W. & Briggs, J. A. G. in Methods in Enzymology (ed. Crowther, R. A.) Ch. 13, 329–367 (Academic, 2016).
Böhning, J. & Bharat, T. A. M. Prog. Biophys. Mol. Biol. 160, 97–103 (2021).
Frangakis, A. S. et al. Proc. Natl Acad. Sci. USA 99, 14153–14158 (2002).
de Teresa, I. et al. Nat. Methods https://doi.org/10.1038/s41592-022-01746-2 (2022).
Moebel, E. et al. Nat. Methods 18, 1386–1394 (2021).
Rice, G., Wagner, T., Stabrin, M. & Raunser, S. Preprint at bioRxiv https://doi.org/10.1101/2022.06.24.497279 (2022).
Lucas, B. A. et al. eLife 10, e68946 (2021).
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Smith, O.E.R., Bharat, T.A.M. Seeing the wood for the trees. Nat Methods 20, 183–184 (2023). https://doi.org/10.1038/s41592-022-01741-7
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DOI: https://doi.org/10.1038/s41592-022-01741-7