https://3demmethods.i2pc.es/index.php?action=history&feed=atom&title=2025Peng_DiamTR 2026-05-01T07:51:24Z Revision history for this page on the wiki MediaWiki 1.44.2 https://3demmethods.i2pc.es/index.php?title=2025Peng_DiamTR&diff=5124&oldid=prev 2025-12-29T09:29:51Z

<p>Created page with &quot;== Citation == Peng, R., Elkhaligy, H., Grant, T. and Stagg, S.M. 2025. DiameTR: A cryo-EM tool for diameter sorting of tubular samples. J. Structural Biology: X. (2025), 100136. == Abstract == Tubular structures are ubiquitous in biological systems and have been a focal point of cryo-electron microscopy (cryo-EM) structural analysis since the technique’s inception. A critical step in processing tubular cryo-EM data is particle classification by diameter, as uniform...&quot;</p> <p><b>New page</b></p><div>== Citation ==<br /> <br /> Peng, R., Elkhaligy, H., Grant, T. and Stagg, S.M. 2025. DiameTR: A cryo-EM tool for diameter sorting of tubular samples. J. Structural Biology: X. (2025), 100136.<br /> <br /> == Abstract ==<br /> <br /> Tubular structures are ubiquitous in biological systems and have been a focal point of cryo-electron microscopy (cryo-EM) structural analysis since the technique’s<br /> inception. A critical step in processing tubular cryo-EM data is particle classification by diameter, as uniformity in diameter is a prerequisite for high-resolution threedimensional<br /> reconstructions. Conventional methods rely on cross-correlation-based algorithms, which require prior knowledge to generate reference images, or<br /> iterative two-dimensional (2D) classification, that align and cluster particles into a predefined number of classes—a process that is both time-consuming and subjective.<br /> To address these limitations, we developed diameTR, a computational tool that rapidly determines tubular diameters in a prior knowledge-free and referencefree<br /> manner using GPU-accelerated processing on a per-particle basis. When applied to homogeneous datasets, diameTR yields narrow diameter distributions aligning<br /> closely with published values. For heterogeneous samples, it enables the separation of subsets with distinct diameters, validated by 2D averaging. Notably, diameTR<br /> identified an unreported smaller diameter subset of particles with new helical symmetry parameters in the previously published KpFtsZ-Monobody dataset.<br /> Collectively, diameTR represents a robust, efficient solution for diameter determination in tubular cryo-EM samples, eliminating the need for extensive human<br /> intervention while significantly accelerating processing.<br /> <br /> == Keywords ==<br /> <br /> == Links ==<br /> <br /> https://www.sciencedirect.com/science/article/pii/S2590152425000170<br /> <br /> == Related software ==<br /> <br /> == Related methods ==<br /> <br /> == Comments ==</div>

WikiSysop