References

Bibliography of works referenced in the CryoNAV documentation.

Cryo-electron tomography

Baumeister, W. (2002). Electron tomography: towards visualizing the molecular organization of the cytoplasm. Current Opinion in Structural Biology, 12(5), 679-684.
Lucic, V., Forster, F., & Baumeister, W. (2005). Structural studies by electron tomography: from cells to molecules. Annual Review of Biochemistry, 74, 833-865.

Kremer, J. R., Mastronarde, D. N., & McIntosh, J. R. (1996). Computer visualization of three-dimensional image data using IMOD. Journal of Structural Biology, 116(1), 71-76.
Mastronarde, D. N., & Held, S. R. (2017). Automated tilt series alignment and tomographic reconstruction in IMOD. Journal of Structural Biology, 197(2), 102-113.
Scheres, S. H. W. (2012). RELION: implementation of a Bayesian approach to cryo-EM structure determination. Journal of Structural Biology, 180(3), 519-530.
Punjani, A., Rubinstein, J. L., Fleet, D. J., & Brubaker, M. A. (2017). cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination. Nature Methods, 14, 290-296.
de la Rosa-Trevin, J. M., Quintana, A., del Cano, L., et al. (2016). Scipion: A software framework toward integration, reproducibility and validation in 3D electron microscopy. Journal of Structural Biology, 195(1), 93-99.
Tegunov, D., & Cramer, P. (2019). Real-time cryo-electron microscopy data preprocessing with Warp. Nature Methods, 16, 1146-1152.
Tegunov, D., Xue, L., Dienemann, C., Cramer, P., & Mahamid, J. (2021). Multi-particle cryo-EM refinement with M visualizes ribosome-antibiotic complex at 3.5 Angstrom in cells. Nature Methods, 18, 186-193.
Liu, H.-F., Zhou, Y., Huang, Q., et al. (2023). nextPYP: A comprehensive and scalable platform for characterizing protein variability in-situ using single-particle cryo-electron tomography. Nature Methods, 20, 1909-1919.

Buchholz, T.-O., Jordan, M., Pigino, G., & Jug, F. (2019). Cryo-CARE: Content-aware image restoration for cryo-transmission electron microscopy data. Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI), 502-506.
Wiedemann, S., & Heckel, R. (2024). A deep learning method for simultaneous denoising and missing wedge reconstruction in cryogenic electron tomography. Nature Communications, 15, 8255.