https://3demmethods.i2pc.es/index.php?action=history&feed=atom&title=2022Liu_Isonet 2026-05-24T21:06:50Z Revision history for this page on the wiki MediaWiki 1.44.2 https://3demmethods.i2pc.es/index.php?title=2022Liu_Isonet&diff=4349&oldid=prev 2023-06-26T09:10:51Z

<p>Created page with &quot;== Citation == Liu, Yun-Tao / Zhang, Heng / Wang, Hui / Tao, Chang-Lu / Bi, Guo-Qiang / Zhou, Z. Hong. Isotropic reconstruction for electron tomography with deep learning. 20...&quot;</p> <p><b>New page</b></p><div>== Citation ==<br /> <br /> Liu, Yun-Tao / Zhang, Heng / Wang, Hui / Tao, Chang-Lu / Bi, Guo-Qiang / Zhou, Z. Hong. Isotropic reconstruction for electron tomography with deep learning. 2022. Nature Communications, Vol. 13, No. 1, p. 6482 <br /> <br /> == Abstract ==<br /> <br /> Cryogenic electron tomography (cryoET) allows visualization of cellular<br /> structures in situ. However, anisotropic resolution arising from the intrinsic<br /> “missing-wedge” problem has presented major challenges in visualization<br /> and interpretation of tomograms. Here, we have developed IsoNet, a deep<br /> learning-based software package that iteratively reconstructs the missingwedge<br /> information and increases signal-to-noise ratio, using the knowledge<br /> learned from raw tomograms. Without the need for sub-tomogram averaging,<br /> IsoNet generates tomograms with significantly reduced resolution<br /> anisotropy. Applications of IsoNet to three representative types of cryoET<br /> data demonstrate greatly improved structural interpretability: resolving<br /> lattice defects in immature HIV particles, establishing architecture of the<br /> paraflagellar rod in Eukaryotic flagella, and identifying heptagon-containing<br /> clathrin cages inside a neuronal synapse of cultured cells. Therefore, by<br /> overcoming two fundamental limitations of cryoET, IsoNet enables functional<br /> interpretation of cellular tomograms without sub-tomogram averaging.<br /> Its application to high-resolution cellular tomograms should also help<br /> identify differently oriented complexes of the same kind for sub-tomogram<br /> averaging.<br /> <br /> == Keywords ==<br /> <br /> == Links ==<br /> <br /> https://www.nature.com/articles/s41467-022-33957-8<br /> <br /> == Related software ==<br /> <br /> == Related methods ==<br /> <br /> == Comments ==</div>

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