3DEM-Methods - Recent changes [en]

2013Ruskin DQE

WikiSysop — Thu, 23 Jul 2026 06:31:03 GMT

Created page with "== Citation == Ruskin, A.I., Yu, Z. and Grigorieff, N. 2013. Quantitative characterization of electron detectors for transmission electron microscopy. J. Structural biology. 184, 3 (2013), 385–393. == Abstract == A new generation of direct electron detectors for transmission electron microscopy (TEM) promises significant improvement over previous detectors in terms of their modulation transfer function (MTF) and detective quantum efficiency (DQE). However, the perfo..."

New page

== Citation ==

Ruskin, A.I., Yu, Z. and Grigorieff, N. 2013. Quantitative characterization of electron detectors for transmission electron microscopy. J. Structural biology. 184, 3 (2013), 385–393.

== Abstract ==

A new generation of direct electron detectors for transmission electron microscopy (TEM) promises significant
improvement over previous detectors in terms of their modulation transfer function (MTF) and
detective quantum efficiency (DQE). However, the performance of these new detectors needs to be carefully
monitored in order to optimize imaging conditions and check for degradation over time. We have
developed an easy-to-use software tool, FindDQE, to measure MTF and DQE of electron detectors using
images of a microscope’s built-in beam stop. Using this software, we have determined the DQE curves
of four direct electron detectors currently available: the Gatan K2 Summit, the FEI Falcon I and II, and
the Direct Electron DE-12, under a variety of total dose and dose rate conditions. We have additionally
measured the curves for the Gatan US4000 and TVIPS TemCam-F416 scintillator-based cameras. We compare
the results from our new method with published curves.

== Keywords ==

== Links ==

https://www.sciencedirect.com/science/article/pii/S1047847713002815

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WikiSysop — Thu, 23 Jul 2026 06:27:38 GMT

Image formation

← Older revision		Revision as of 06:27, 23 July 2026
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	\| Paper		\| Paper
	\| [[~~2013Shigematsu H_Noisemodels~~]]		\| [[2013Li X K2 noisemodels]]
	\| ~~Noise models and cryo-EM drift correction~~ with ~~a direct~~-~~electron~~ camera		\| Influence of electron dose rate on electron counting images recorded with the K2 camera
			\|-

			\| Paper
			\| [[2013Ruskin_DQE]]
			\| Measurement of the DQE, camera MTF, and the noise power spectrum of cameras
	\|-		\|-

	\| Paper		\| Paper
	\| [[~~2013Li X K2 noisemodels~~]]		\| [[2013Shigematsu H_Noisemodels]]
	\| ~~Influence of~~ electron ~~dose rate on electron counting images recorded with the K2~~ camera		\| Noise models and cryo-EM drift correction with a direct-electron camera
	\|-		\|-

2026Motta Dublins

WikiSysop — Thu, 23 Jul 2026 06:19:35 GMT

Created page with "== Citation == Motta Alves, G., Andrews, T., McBean, P., Wells, T., El-Gomati, M.M., Burkhalter, S., Schulze-Briese, C., Zambon, P., McMullan, G., Henderson, R. and others 2026. The Dublin lens: a Cc= 1.0 mm objective lens intended for CryoEM at 100 keV. Methods in Microscopy. 3, 1 (2026), 19–25. == Abstract == We have designed, fabricated and tested a lens with a chromatic aberration coefficient (Cc) of 1.0 mm, a 4.0 mm pole-gap and 2.0 mm bore that is wide enough..."

New page

== Citation ==

Motta Alves, G., Andrews, T., McBean, P., Wells, T., El-Gomati, M.M., Burkhalter, S., Schulze-Briese, C., Zambon, P., McMullan, G., Henderson, R. and others 2026. The Dublin lens: a Cc= 1.0 mm objective lens intended for CryoEM at 100 keV. Methods in Microscopy. 3, 1 (2026), 19–25.

== Abstract ==

We have designed, fabricated and tested a lens with a chromatic aberration coefficient (Cc) of 1.0 mm, a 4.0 mm pole-gap and 2.0 mm bore that is wide enough to accommodate an anti-contamination system and an objective aperture. This lens extends the temporal-coherence envelope of the electron microscope beyond 2 Å, using a low-cost Schottky FEG. We hope that this lens design can be used to improve all 100 keV electron microscopes designed for single-particle electron cryomicroscopy (cryoEM).

== Keywords ==

== Links ==

https://www.degruyterbrill.com/document/doi/10.1515/mim-2025-0019/html

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== Comments ==

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WikiSysop — Thu, 23 Jul 2026 06:18:54 GMT

Image formation

← Older revision		Revision as of 06:18, 23 July 2026
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	\| [[2026Heymann_Ewald]]		\| [[2026Heymann_Ewald]]
	\| The relationship between the Ewald sphere and exit wave explored using focal series electron micrographs		\| The relationship between the Ewald sphere and exit wave explored using focal series electron micrographs
			\|-

			\| Paper
			\| [[2026Motta_Dublins]]
			\| Dublin lens for 100kV microscopes
	\|-		\|-

2024Wang CryoSeek

WikiSysop — Wed, 22 Jul 2026 06:46:51 GMT

Created page with "== Citation == Wang, T., Li, Z., Xu, K., Huang, W., Huang, G., Zhang, Q.C. and Yan, N. 2024. CryoSeek: A strategy for bioentity discovery using cryoelectron microscopy. Proceedings of the National Academy of Sciences. 121, 42 (2024), e2417046121. == Abstract == Structural biology is experiencing a paradigm shift from targeted structural determination to structure-guided discovery of previously uncharacterized bioentities. We employed cryoelectron microscopy (cryo-EM)..."

New page

== Citation ==

Wang, T., Li, Z., Xu, K., Huang, W., Huang, G., Zhang, Q.C. and Yan, N. 2024. CryoSeek: A strategy for bioentity discovery using cryoelectron microscopy. Proceedings of the National Academy of Sciences. 121, 42 (2024), e2417046121.

== Abstract ==

Structural biology is experiencing a paradigm shift from targeted structural determination
to structure-guided
discovery of previously uncharacterized bioentities. We
employed cryoelectron microscopy (cryo-EM)
to analyze filtered water samples collected
from the Tsinghua Lotus Pond. Here, we report the structural determination and
characterization of two highly similar helical fibrils, named TLP-1a
and TLP-1b,
each
approximately 8 nm in diameter with a 15-Å
wide tunnel. These fibrils are assembled
from a similar protein protomer, whose structure was conveniently automodeled in
CryoNet. The protomer structure does not match any available experimental structures,
but shares the same fold as many predicted structures of unknown functions.
The amino-terminal
β strand of protomer n + 4 inserts into a cleft in protomer n to
complete an immunoglobulin (Ig)-like
domain. This packing mechanism, known as
donor-strand
exchange (DSE), has been observed in several bacterial pilus assemblies,
wherein the donor is protomer n + 1. Despite distinct shape and thickness, this reminiscence
suggests that TLP-1a/
b fibrils may represent uncharacterized bacterial pili. Our
study demonstrates an emerging paradigm in structural biology, where high-resolution
structural determination precedes and drives the identification and characterization of
completely unknown objects.

== Keywords ==

== Links ==

https://www.pnas.org/doi/abs/10.1073/pnas.2417046121

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WikiSysop — Wed, 22 Jul 2026 06:46:11 GMT

Software

← Older revision		Revision as of 06:46, 22 July 2026
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	\| [[2024Vuillemot_MDSPACE]]		\| [[2024Vuillemot_MDSPACE]]
	\| MDSpace and MDTomo to analyze continuous heterogeneity		\| MDSpace and MDTomo to analyze continuous heterogeneity
			\|-

			\| Paper
			\| [[2024Wang_CryoSeek]]
			\| CryoSeek: protein identification with CryoEM, modelling and Mass spectroscopy
	\|-		\|-

2026Petrov Laser

WikiSysop — Thu, 09 Jul 2026 06:43:31 GMT

Created page with "== Citation == Petrov, P.N., Zhang, J.T., Remis, J., Axelrod, J.J., Cheng, H., Cooper, E.S., Hicklin, I.K., Sandhaus, S., Schnurr, C., Glaeser, R.M. and others 2026. Laser phase plate improves structure determination of small proteins by cryo-EM. Science. (2026), eaeh0665. == Abstract == Phase plates can in principle overcome the poor image contrast in electron cryo–microscopy (cryo-EM) and the resulting limits on the structural reconstruction of small proteins. How..."

New page

== Citation ==

Petrov, P.N., Zhang, J.T., Remis, J., Axelrod, J.J., Cheng, H., Cooper, E.S., Hicklin, I.K., Sandhaus, S., Schnurr, C., Glaeser, R.M. and others 2026. Laser phase plate improves structure determination of small proteins by cryo-EM. Science. (2026), eaeh0665.

== Abstract ==

Phase plates can in principle overcome the poor image contrast in electron cryo–microscopy (cryo-EM) and the resulting limits
on the structural reconstruction of small proteins. However, previous designs have been unstable and compromised the highresolution
signal. They have thus been unable to surpass results achieved by standard cryo-EM. Here, we show that the laser
phase plate (LPP), installed in a custom, modern Titan Krios microscope, enhances the resolution in single-particle reconstruction
of small proteins by improving specimen-motion correction, recovery of information from the early frames, as well as particle
visualization, 3D classification, and alignment. These advances use standard defocus ranges and reconstruction procedures, but
open the door to LPP-tailored protocols offering further improvements by leveraging the LPP demonstrated here.

== Keywords ==

== Links ==

https://www.science.org/doi/full/10.1126/science.aeh0665

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WikiSysop — Thu, 09 Jul 2026 06:42:39 GMT

Image formation

← Older revision		Revision as of 06:42, 9 July 2026
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	\| [[2026Obrien_CryoJax]]		\| [[2026Obrien_CryoJax]]
	\| CryoJAX: Simulation of SPA images from atomic coordinates		\| CryoJAX: Simulation of SPA images from atomic coordinates
			\|-

			\| Paper
			\| [[2026Petrov_Laser]]
			\| Laser phase plates
	\|-		\|-

2026Subramaniam Review

WikiSysop — Thu, 09 Jul 2026 06:24:53 GMT

Created page with "== Citation == Subramaniam, S., Kühlbrandt, W. and Henderson, R. 2026. Cryo-EM: the revolution continues. IUCrJ. 13, 4 (2026). == Abstract == The near-universal adoption of electron cryo-microscopy (cryo-EM) by structural and cell biologists has led to exponential growth of the field, especially over the last two decades, with a doubling in the number of deposited electronmicroscopy density maps every 2.5 years. This exponential growth has changed in recent years to..."

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== Citation ==

Subramaniam, S., Kühlbrandt, W. and Henderson, R. 2026. Cryo-EM: the revolution continues. IUCrJ. 13, 4 (2026).

== Abstract ==

The near-universal adoption of electron cryo-microscopy (cryo-EM) by structural
and cell biologists has led to exponential growth of the field, especially over
the last two decades, with a doubling in the number of deposited electronmicroscopy
density maps every 2.5 years. This exponential growth has changed
in recent years to become linear. Cryo-EM methods are now able to contribute
to our structural understanding of biological complexity ranging from atomic
resolution maps of assemblies of multiprotein complexes to in situ investigation
of protein structures in the context of intact cells, snapshots of multiple
conformations and insights into fundamental chemical mechanisms underlying
biological function. Combined with dramatic advances in artificial intelligence,
the increasing democratization and implementation of cryo-EM appears poised
to drive a new revolution in digital biology.

== Keywords ==

== Links ==

https://journals.iucr.org/m/issues/2026/04/00/hi5656/index.html

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WikiSysop — Thu, 09 Jul 2026 06:24:12 GMT

Books and reviews

← Older revision		Revision as of 06:24, 9 July 2026
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	\| [[2026Lin_HDX]]		\| [[2026Lin_HDX]]
	\| Comment on the complementarity of HDX-MS studies for heterogeneous particles		\| Comment on the complementarity of HDX-MS studies for heterogeneous particles
			\|-

			\| Paper
			\| [[2026Subramaniam_Review]]
			\| Review on the general state of cryoEM
	\|-		\|-

2026Chrencik SBDD

WikiSysop — Tue, 07 Jul 2026 06:31:08 GMT

Created page with "== Citation == Chrencik, J.E., Su, H.-P., Gomez Llorente, Y., Palte, R.L., Klein, D.J., Hayes, R.P., Antine, S.P., Asmar-Rovira, G.A., Bertoletti, N., Byrne, N.J. and others 2026. The evolving role of structural biology in pharma: integration of X-ray crystallography, cryo-electron microscopy and beyond. Biological Crystallography. 82, 6 (2026). == Abstract == Structural biology has fundamentally influenced pharmaceutical research and development at Merck Sharp & Dohm..."

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== Citation ==

Chrencik, J.E., Su, H.-P., Gomez Llorente, Y., Palte, R.L., Klein, D.J., Hayes, R.P., Antine, S.P., Asmar-Rovira, G.A., Bertoletti, N., Byrne, N.J. and others 2026. The evolving role of structural biology in pharma: integration of X-ray crystallography, cryo-electron microscopy and beyond. Biological Crystallography. 82, 6 (2026).

== Abstract ==

Structural biology has fundamentally influenced pharmaceutical research and
development at Merck Sharp & Dohme LLC, Rahway, New Jersey, USA,
progressing from pioneering macromolecular crystallography in the 1980s to a
fully integrated platform that today encompasses X-ray crystallography, cryoelectron
microscopy, micro-electron diffraction and cryo-electron tomography.
In this review, we present a comprehensive overview of how these complementary
methods have advanced drug discovery across diverse therapeutic
areas. We illustrate how atomic to cellular structural insights inform drug
discovery and development, from target identification and validation, hit
finding, lead identification through lead optimization and clinical progression.
Furthermore, we describe how structural biology techniques aid in formulation
strategies of antibodies and vaccines. Finally, we highlight the growing integration
of ex situ and in situ approaches as a paradigm shift towards elucidating
drug mechanisms in native cellular contexts, a transition poised to accelerate the
discovery and development of next-generation therapeutics.

== Keywords ==

== Links ==

https://journals.iucr.org/d/issues/2026/06/00/raj5002/index.html

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WikiSysop — Tue, 07 Jul 2026 06:30:26 GMT

Books and reviews

← Older revision		Revision as of 06:30, 7 July 2026
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	\| [[2025Zhu_Quality]]		\| [[2025Zhu_Quality]]
	\| Review of AI-based quality assessment of SPA maps		\| Review of AI-based quality assessment of SPA maps
			\|-

			\| Paper
			\| [[2026Chrencik_SBDD]]
			\| Review of the role of Structural Biology in Pharma
	\|-		\|-

2025Starynska Membrane

WikiSysop — Tue, 07 Jul 2026 06:17:51 GMT

Created page with "== Citation == Starynska, A., Cameron, C.J., Sigworth, F.J. and Tagare, H.D. 2026. Automated Membrane Detection and Subtraction for Structure Determination of Membrane Proteins in Cryogenic Electron Microscopy. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2026), 6553–6562. == Abstract == High-resolution cryo-electron microscopy (cryo-EM) reconstruction of membrane proteins often requires the bilayer membrane containing the prote..."

New page

== Citation ==

Starynska, A., Cameron, C.J., Sigworth, F.J. and Tagare, H.D. 2026. Automated Membrane Detection and Subtraction for Structure Determination of Membrane Proteins in Cryogenic Electron Microscopy. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2026), 6553–6562.

== Abstract ==

High-resolution cryo-electron microscopy (cryo-EM) reconstruction
of membrane proteins often requires the bilayer
membrane containing the protein to be subtracted
from the image. We propose a two-step machine learning
framework for this task: (1) membrane detection, which
identifies the bilayer membrane, and (2) membrane subtraction,
which digitally removes the detected membrane
from the cryo-EM image. Recent work has introduced algorithms
for membrane detection, but membrane subtraction
remains relatively underexplored. Here, we present
a novel unsupervised approach for membrane subtraction
which computes a smooth estimate of the membrane that
can be subtracted from the original cryo-EM image. Experimental
results show that our method outperforms existing
membrane subtraction alternatives and enables reliable 3D
reconstruction of membrane proteins.

== Keywords ==

== Links ==

https://openaccess.thecvf.com/content/CVPR2026W/CVMI/html/Starynska_Automated_Membrane_Detection_and_Subtraction_for_Structure_Determination_of_Membrane_CVPRW_2026_paper.html

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WikiSysop — Tue, 07 Jul 2026 06:16:56 GMT

2D Preprocessing

← Older revision		Revision as of 06:16, 7 July 2026
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	\| [[2025Yan_Foundation]]		\| [[2025Yan_Foundation]]
	\| A comprehensive foundation model for cryo-EM image processing (deep learning)		\| A comprehensive foundation model for cryo-EM image processing (deep learning)
			\|-

			\| Paper
			\| [[2025Starynska_Membrane]]
			\| Membrane detection and substraction from micrographs
	\|-		\|-

2026Gao CryoKRAQEN

WikiSysop — Tue, 07 Jul 2026 05:55:08 GMT

Created page with "== Citation == Gao, W., Wu, Y. and He, X. 2026. CryoKRAQEN: Kernel-Regularized Annealing for Quantized Embedding Networks in Cryo-EM Heterogeneous Reconstruction. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2026), 28298–28307. == Abstract == Heterogeneous reconstruction in cryo-electron microscopy (Cryo-EM) is fundamental for understanding macromolecular structural diversity, yet remains challenging due to extreme noise, contin..."

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== Citation ==

Gao, W., Wu, Y. and He, X. 2026. CryoKRAQEN: Kernel-Regularized Annealing for Quantized Embedding Networks in Cryo-EM Heterogeneous Reconstruction. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2026), 28298–28307.

== Abstract ==

Heterogeneous reconstruction in cryo-electron microscopy
(Cryo-EM) is fundamental for understanding macromolecular
structural diversity, yet remains challenging due to
extreme noise, continuous conformational changes, and
ambiguous image-to-structure mappings. Existing neural
approaches often rely on encoder–decoder pipelines or
fixed codebooks, which can be computationally demanding
or struggle with complex heterogeneity. We propose
CryoKRAQEN, a decoder-only framework that integrates
triplane implicit representations with kernel-guided latent
assignment and quantized embeddings to improve stability
and structural discrimination. The method avoids encoder
dependencies and mitigates collapse during training,
enabling accurate modeling of both conformational and
compositional variations. Across diverse Cryo-EM benchmarks,
CryoKRAQEN delivers competitive performance,
robust reconstructions, and interpretable latent organization
compared to state-of-the-art neural and classical methods.
The project page is available at CryoKRAQEN.

== Keywords ==

== Links ==

https://openaccess.thecvf.com/content/CVPR2026/html/Gao_CryoKRAQEN_Kernel-Regularized_Annealing_for_Quantized_Embedding_Networks_in_Cryo-EM_Heterogeneous_CVPR_2026_paper.html

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WikiSysop — Tue, 07 Jul 2026 05:54:30 GMT

3D Heterogeneity

← Older revision		Revision as of 05:54, 7 July 2026
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	\| [[2026Evans_Counting]]		\| [[2026Evans_Counting]]
	\| Counting particles in cryo-electron microscopy may result in incorrect population estimates.		\| Counting particles in cryo-electron microscopy may result in incorrect population estimates.
			\|-

			\| Conference
			\| [[2026Gao_CryoKRAQEN]]
			\| CryoKRAQEN: Kernel-Regularized Annealing for Quantized Embedding Networks in Cryo-EM Heterogeneous Reconstruction
	\|-		\|-