https://3demmethods.i2pc.es/index.php?action=history&feed=atom&title=2024Cruz_Template 2026-05-24T21:06:59Z Revision history for this page on the wiki MediaWiki 1.44.2 https://3demmethods.i2pc.es/index.php?title=2024Cruz_Template&diff=4674&oldid=prev 2024-08-12T07:14:26Z

<p>Created page with &quot;== Citation == Cruz-León, Sergio / Majtner, Tomáš / Hoffmann, Patrick / Kreysing, Jan P. / Tuijtel, Maarten W. / Schaefer, Stefan L. / Geißler, Katharina / Beck, Martin / Turoňová, Beata / Hummer, Gerhard. High-confidence 3D template matching for cryo-electron tomography. 2024. Biophysical Journal, Vol. 123, No. 3, p. 183a == Abstract == Visual proteomics attempts to build atlases of the molecular content of cells but the automated annotation of cryo electron to...&quot;</p> <p><b>New page</b></p><div>== Citation ==<br /> <br /> Cruz-León, Sergio / Majtner, Tomáš / Hoffmann, Patrick / Kreysing, Jan P. / Tuijtel, Maarten W. / Schaefer, Stefan L. / Geißler, Katharina / Beck, Martin / Turoňová, Beata / Hummer, Gerhard. High-confidence 3D template matching for cryo-electron tomography. 2024. Biophysical Journal, Vol. 123, No. 3, p. 183a<br /> <br /> == Abstract ==<br /> <br /> Visual proteomics attempts to build atlases of the molecular content of cells<br /> but the automated annotation of cryo electron tomograms remains challenging.<br /> Template matching (TM) and methods based on machine learning detect<br /> structural signatures of macromolecules. However, their applicability remains<br /> limited in terms of both the abundance and size of the molecular targets. Here<br /> we show that the performance of TM is greatly improved by using template specific<br /> search parameter optimization and by including higher-resolution<br /> information. We establish a TM pipeline with systematically tuned parameters<br /> for the automated, objective and comprehensive identification of structures<br /> with confidence 10 to 100-fold above the noise level. We demonstrate high fidelity<br /> and high-confidence localizations of nuclear pore complexes, vaults,<br /> ribosomes, proteasomes, fatty acid synthases, lipid membranes and microtubules,<br /> and individual subunits inside crowded eukaryotic cells. We provide<br /> software tools for the generic implementation of our method that is broadly<br /> applicable towards realizing visual proteomics.<br /> <br /> == Keywords ==<br /> <br /> == Links ==<br /> <br /> https://www.cell.com/biophysj/fulltext/S0006-3495(23)01890-8<br /> <br /> == Related software ==<br /> <br /> == Related methods ==<br /> <br /> == Comments ==</div>

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