#CryoSPARC v4.7 is out! 🚀 .Featuring a new automatic Micrograph Junk Detector that labels and rejects contaminants, new tools for curating subsets of particles, performance and stability fixes, and more! .Full changelog: #cryoEM

RT @OliBClarke: New story - a joint effort with the Vallese lab at ASRC - in which we solve the #cryoem structures of endogenous RBC stoma….

RT @nchembio: Disulfide-based dimerization of modified nanobody scaffolds enables higher-order assembly for high-resolution cryo-EM structu….

RT @generate_biomed: We’re scaling structure as a core capability in AI-native drug design. #TeamGenerate is searching for an Executive Di….

Flexibility can be frustrating when processing a #cryoEM dataset. If your target has a wobbly domain, check out our new case study on FaNaC1 for continuous heterogeneity tips in #CryoSPARC!.

RT @edward_eng: Looking forward to seeing everyone tomorrow at #MM2025 PMCX61: Transformative. High-Resolution Cryo-Electron Microscopy (3D….

When particles have orientation bias, the resulting maps are often streaked along the missing directions. In this case study, we cover why orientation bias produces anisotropic #cryoEM maps and how you may be able to recover from it!.

Link here!

Working with symmetric or pseudosymmetric particles in #cryoEM? . This TRPV5 and CaM case study includes practical considerations for using symmetry relaxation and 3D classification when analyzing a pseudosymmetric particle in #CryoSPARC!

Looking for a deep dive into 2D classification in #cryoEM?. These recent guide pages cover practical aspects & parameter choices when running these jobs in #CryoSPARC, along with the theory behind expectation maximization: and

RT @OliBClarke: New story - the structure of the Vault cap at 2.3 Å! Fantastic work by Huan Li (@huanli00). For more details, read the prep….

RT @edward_eng: Save the date! October 9-10, 2025 @asrc_gc SBI & @NYSBC_Science will host our 3rd NYC Integrative Structural Biology sympos….

Grappling with poorly-resolved ligand binding sites in #cryoEM maps?.Check out our new case study on a peptide ligand-bound GPCR showing how practical tips and features in #CryoSPARC v4.7 improve locally refined map quality & reveal clearer ligand density!.

Are you new to #CryoEM, or looking for a review of the basics? .You might enjoy our TRPV1 case study! It covers preprocessing, particle curation, refinement, and more! You can also test your skills with the advanced exercises at the end of the study.

8/ A huge thanks to S2C2 for organizing and recording the workshop, and to all participants for your engagement! .Check out other talks on S2C2’s website: @S2CryoEMCenter @SLAClab.

7/ The final video discusses two ways of working with continuous heterogeneity in #CryoSPARC (3D Variability Analysis & 3D Flexible Refinement), and covers both theoretical workings and practical considerations for inputs and parameter choices.

6/ The fifth video presents the benefits and drawbacks of various methods of handling discrete heterogeneity, using a FaNaC1 dataset as an example.

5/ In the fourth video, we discuss how we processed an Encapsulated Ferritin sample with non-point-group symmetry to high resolution, including using several different jobs to perform a “custom symmetry expansion”.

4/ The third video covers important considerations and potential pitfalls when working with symmetric samples, using the TRPV5 ion channel as an example.

3/ The second video presents a “standard workflow” using TRPV1, meant to be a useful starting workflow for most single-particle datasets. Of course, there are many alternate workflows which will be just as effective!.