{"batchcomplete":"","continue":{"lecontinue":"20260821052940|3665","continue":"-||"},"query":{"logevents":[{"logid":3675,"ns":0,"title":"2025Vivas iceFinder","pageid":3173,"logpage":3173,"revid":5287,"params":{},"type":"create","action":"create","user":"Vilas","timestamp":"2026-09-26T15:37:11Z","comment":"Created page with \"== Citation == A. Vivas-Lago, D. Casta\u00f1o-D\u00edez, Few-shot learning for non-vitrified ice segmentation, Scientific Reports, 15, 1, 5501, (2025).  == Abstract == This study introduces Ice Finder, a novel tool for quantifying crystalline ice in cryo-electron tomography, addressing a critical gap in existing methodologies. We present the first application of the meta-learning paradigm to this field, demonstrating that diverse tomographic tasks across datasets can be unified...\""},{"logid":3674,"ns":0,"title":"2026Poudel CryoFSL","pageid":3172,"logpage":3172,"revid":5285,"params":{},"type":"create","action":"create","user":"WikiSysop","timestamp":"2026-09-24T05:19:54Z","comment":"Created page with \"== Citation ==  Poudel, B., Gyawali, R., Dhakal, A., Cheng, J. and Xu, D. 2026. CryoFSL: an annotation-efficient, few-shot learning framework for robust protein particle picking in cryo-electron microscopy micrographs. Briefings in Bioinformatics. 27, 3 (2026), bbag285.  == Abstract ==  Accurate identification of protein particles in cryo-electron microscopy (cryo-EM) micrographs is crucial for high-resolution structure determination, but remains challenging due to the h...\""},{"logid":3673,"ns":0,"title":"2021Chen Ewald","pageid":3171,"logpage":3171,"revid":5283,"params":{},"type":"create","action":"create","user":"WikiSysop","timestamp":"2026-09-24T05:02:21Z","comment":"Created page with \"== Citation ==  Chen, J.P., Schmidt, K.E., Spence, J.C. and Kirian, R.A. 2021. A new solution to the curved Ewald sphere problem for 3D image reconstruction in electron microscopy. Ultramicroscopy. 224, (2021), 113234.  == Abstract ==  We develop an algorithm capable of imaging a three-dimensional object given a collection of two-dimensional images of that object that are significantly influenced by the curvature of the Ewald sphere. These two-dimensional images cannot b...\""},{"logid":3672,"ns":0,"title":"2026Burton PASR","pageid":3170,"logpage":3170,"revid":5281,"params":{},"type":"create","action":"create","user":"WikiSysop","timestamp":"2026-09-18T05:08:06Z","comment":"Created page with \"== Citation ==  Burton Smith, R. and Murata, K. 2026. Post-acquisition super resolution for cryo-electron microscopy. IUCrJ. 13, 5 (2026).  == Abstract ==  Recently, reports have demonstrated achieving resolutions beyond the physical Nyquist limit using super resolution acquisition. Here, we demonstrate exceeding this limitation by pre-processing the raw micrograph movies from counting mode data that have already reached the physical Nyquist reconstruction resolution. To...\""},{"logid":3671,"ns":0,"title":"2026Klaholz Concepts","pageid":3169,"logpage":3169,"revid":5279,"params":{},"type":"create","action":"create","user":"WikiSysop","timestamp":"2026-09-17T05:54:07Z","comment":"Created page with \"== Citation ==  Klaholz, B.P. 2026. A discussion of cryo-EM terminology as the outreach and number of PDB entries expand. IUCrJ. 13, 5 (2026).  == Abstract ==  Cryo electron microscopy (cryo-EM) has made great advances in the last decade, progressively increasing its impact in structural biology as a key method to address molecular structures and mechanisms of various macromolecular complexes. Single-particle cryo-EM will soon equal the number of yearly entries in the Pr...\""},{"logid":3670,"ns":0,"title":"2025Xu CryoDataBot","pageid":3168,"logpage":3168,"revid":5277,"params":{},"type":"create","action":"create","user":"WikiSysop","timestamp":"2026-09-15T09:15:35Z","comment":"Created page with \"== Citation ==  Xu, Q., Wu, L., Rebelo, M., Feng, S., Yu, X., Farheen, F., Kihara, D. and Zhou, Z.H. 2025. CryoDataBot: a pipeline to curate cryoEM datasets for AI-driven structural biology. GigaScience. 14, (2025), giaf127.  == Abstract ==  Cryogenic electron microscopy (cryoEM) has revolutionized structural biology by enabling atomic-resolution visualization of biomacromolecules. With artificial intelligence (AI) increasing role in newly developed cryoEM tools, task-sp...\""},{"logid":3669,"ns":0,"title":"2026Sun QwenCryoMarker","pageid":3167,"logpage":3167,"revid":5275,"params":{},"type":"create","action":"create","user":"WikiSysop","timestamp":"2026-09-03T05:57:51Z","comment":"Created page with \"== Citation ==  Sun, Y., Zhao, J., Xu, N., Wang, L., Ding, W. and Li, M. 2026. QwenCryoMarker: a universal post-processing framework for contamination-aware particle cleaning. Acta Crystallographica Sec. D. 82, 9 (2026).  == Abstract ==  Cryo-electron microscopy (cryo-EM) micrographs are frequently contaminated by carbon edges, ice crystals, ethane bubbles and other high-contrast artifacts. These contaminants trigger abundant false positives in automated particle pickers...\""},{"logid":3668,"ns":0,"title":"2026Kreymer EM","pageid":3166,"logpage":3166,"revid":5273,"params":{},"type":"create","action":"create","user":"WikiSysop","timestamp":"2026-08-31T04:37:26Z","comment":"Created page with \"== Citation ==  Kreymer, S., Singer, A. and Bendory, T. 2026. Expectation-maximization for structure determination directly from cryo-em micrographs. Inverse problems and imaging. 27, (2026), 110.  == Abstract ==  A single-particle cryo-electron microscopy (cryo- EM) measurement, called a micrograph, consists of multiple two-dimensional tomographic projections of a three-dimensional (3-D) molecular structure at unknown locations, taken under unknown viewing directions. A...\""},{"logid":3667,"ns":0,"title":"2026Jain ProtAcid","pageid":3165,"logpage":3165,"revid":5271,"params":{},"type":"create","action":"create","user":"WikiSysop","timestamp":"2026-08-24T05:12:03Z","comment":"Created page with \"== Citation ==  Jain, A., Cao, K. and Kihara, D. 2026. Computational approaches for protein\u2013DNA/RNA complex modeling for Cryo-EM maps. Current Protocols. 6, 8 (2026), e70409.  == Abstract ==  Cryogenic electron microscopy (cryo-EM) has become a key method in structural biology for determining macromolecular structures. Numerous computational tools have been developed to build atomic models from cryo-EM density maps. However, relatively few tools are available for model...\""},{"logid":3666,"ns":0,"title":"2025Schafer CryoSift","pageid":3164,"logpage":3164,"revid":5269,"params":{},"type":"create","action":"create","user":"WikiSysop","timestamp":"2026-08-21T05:37:36Z","comment":"Created page with \"== Citation ==  Sch\u00e4fer, J.-H., Calza, A., Hom, K., Damodar, P., Peng, R., Bogdanovi\u0107, N., Lander, G.C., Stagg, S.M. and Cianfrocco, M.A. 2025. CryoSift: an accessible and automated CNN-driven tool for cryo-EM 2D class selection. Acta Crystallographica Sec. F. 81, 12 (2025), 517\u2013526.  == Abstract ==  Single-particle cryo-electron microscopy (cryo-EM) has become an essential tool in structural biology. However, automating repetitive tasks remains an ongoing challenge...\""}]}}