Utz Ermel

Works with local OME-Zarr files, or as a bonus: stream sub-tilt stacks directly from the cryoET Data Portal: cryoetdataportal.czscience.com

Massive thanks to @danielji.bsky.social who did the heavy lifting implementing this over the summer! 🙌

GitHub - czimaginginstitute/zarr-particle-tools: Particle extraction and reconstruction from OME-Zarr tilt series. Particle extraction and reconstruction from OME-Zarr tilt series. - czimaginginstitute/zarr-particle-tools

Hi #teamtomo! Want to use OME-Zarr for your tilt series but can't integrate it with your existing sub-tomogram averaging pipelines?

Try zarr-particle-tools - RELION-style extraction & reconstruction built for OME-Zarr-based workflows!

📦 pip install zarr-particle-tools
🔗 github.com/czimagingins...

Stunning cover to celebrate the incredible work from @loicaroyer.bsky.social's team.

Learn more about Ultrack, a powerful tool for fast, accurate and scalable cell tracking: biohub.org/life-science... 🧪

Biohub launches initiative combining frontier AI & frontier biology The large-scale scientific effort combines frontier AI with frontier biology to accelerate discovery and solve disease.

EvolutionaryScale will be joining forces with Biohub to create the first large-scale scientific initiative combining frontier AI & frontier biology. Together, we're building world-class compute, AI research & state-of-the-art technologies to cure or prevent disease. bit.ly/4nOUGO4

Glushkova, Böhm, & Beck @maxplanck.de develop a publicly available computational method to measure the thickness of biological membranes in cryo-electron tomograms. Analysis of algae & human cells reveals systematic membrane thickness variations within & across organelles rupress.org/jcb/article/...

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Lessons learned from a Kaggle challenge for particle picking in cryo-electron tomography [new]
Kaggle cryo-ET picking: Over-pick tol, aug, & annot key.

🎉 Our paper “MIFA: Metadata, Incentives, Formats and Accessibility guidelines to improve the reuse of AI datasets for bioimage analysis” is out in @natmethods.nature.com!
Community-driven standards to make bioimage data AI-ready & reusable.
👉 www.nature.com/articles/s41... #AI #Bioimaging #FAIRdata

A realistic phantom dataset for benchmarking cryo-ET data annotation - Nature Methods A standardized, realistic phantom dataset consisting of ground-truth annotations for six diverse molecular species is provided as a community resource for cryo-electron-tomography algorithm benchmarki...

Better ML for cryo-ET starts with better benchmarks.

We built a phantom cryo-ET dataset (~500 tomograms) + hosted a Kaggle challenge.

The result: community models beat expert tools.

Read more in the @natmethods.nature.com article that just came out:
🔗 doi.org/10.1038/s415...

GitHub - apeck12/denoiset: An implementation of Noise2Noise for cryoET data An implementation of Noise2Noise for cryoET data. Contribute to apeck12/denoiset development by creating an account on GitHub.

New Title Alert: DenoisET- an implementation of the Noise2Noise algorithm specifically designed for cryoET data denoising.

Learn more here: buff.ly/8i8i87U

#SBGrid #SBGridSoftware #StructualBiology

🦠🧠 MemBrain update! 🧠🦠
We’ve updated our preprint! It now covers the full MemBrain v2 pipeline for end-to-end membrane analysis in #CryoET: segmentation, particle picking, and spatial statistics.
🔗 Preprint: doi.org/10.1101/2024...
🔗 Code: github.com/CellArchLab/...
🧵(1/6) #TeamTomo

Figure 4. MemBrain v2 end-to-end workflow detects periodic phycobilisome organization. A: Raw tomogram slice of EMD-31244. B: Out-of-the-box MemBrain-seg segmentation (light blue). C: A single membrane instance can be visualized in Surforama and manually annotated with GT phycobilisome positions (magenta). D: MemBrain-pick localizes particles (trained with data from C) on all membranes in the tomogram. E: MemBrain-stats computes Ripley’s O statistic using the positions from D with a bin size of 5nm. The distance between peaks (35 nm) was measured to estimate chain unit spacings.

We have updated our #MemBrain v2 preprint with a lot more details about the MemBrain-pick and MemBrain-stats modules, as well as some application examples!

Stay tuned for the upcoming thread by lead author @lorenzlamm.bsky.social! 🧠🧵

#CryoET #TeamTomo
www.biorxiv.org/content/10.1...

Excited to share our preprint on the molecular architecture of heterochromatin in human cells 🧬🔬w/ @jpkreysing.bsky.social, @johannesbetz.bsky.social,
@marinalusic.bsky.social, Turoňová lab, @hummerlab.bsky.social @becklab.bsky.social @mpibp.bsky.social

🔗 Preprint here tinyurl.com/3a74uanv

I'm super happy that our story is now published!
📖 www.science.org/doi/10.1126/...
But what changed compared to the original preprint?

Also, I feel i should post Movie 1 🎥, that inspired the cover. Back when I did the original bluesky thread, movies were not available.

📣 Competition Launch Alert! Locating Bacterial Flagellar Motors 2025 hosted by Brigham Young University.

kaggle.com/competitions/byu-locating-bacterial-flagellar-motors-2025

The kaggle competition may be over, but we remain excited to see solutions from #TeamTomo!

If you're interested in checking whether your algorithm beats the kaggle winners' please don’t hesitate to give it a go and make a submission to the data portal!

A 4-panel image showing tomographic slices and annotations from CZII's object detection challenge.

Now that the competition is closed, we're releasing all 492 runs, including raw data, tomograms and ground truth annotations as a benchmark dataset for the community. Find the datasets here: cryoetdataportal.czscience.com/depositions/...

Results from CZII's #cryoET object detection challenge on kaggle are in!

Participation exceeded our expectations with 931 Teams from 76 countries competing, generating over 27,000 submissions. For an overview check out our post-competition page: cryoetdataportal.czscience.com/competition

Happy to share our manuscript on the in situ visualization of the copia retrotransposon in its final form today published in @cellcellpress.bsky.social www.cell.com/cell/fulltex.... What’s new?

Exciting news! Are you planning to eventually release these beautiful segmentations as well?

Rare cellular events observed in the cryo-ET dataset. Slices through tomograms (left) with corresponding 3D segmentation (middle and right). Right panels show enlarged views of the boxed regions in the middle panels. A) Mitochondrion at the plasma membrane, tethered to microtubules by thin filaments of unknown identity. Segmented classes: nuclear envelope (light blue), nuclear pore complex (dark blue), 80S ribosomes (orange), mitochondrial membranes (dark red), ATP synthase (royal blue), plasma membranes (grey), microtubules (pink), filaments (yellow), endoplasmic reticulum (purple). Zoomed-in panel shows thin filaments running between microtubules and the mitochondrion at the plasma membrane. Note that this tomogram contains two closely appressed cells, and thus, two plasma membranes with cell walls between. B) Mitochondrial fission event with ER membrane interactions. Segmented classes: mitochondrial membranes (dark red), ATP synthase (royal blue), 80S ribosomes (orange), thylakoid membranes (green), PSII (bright yellow), cell wall (grey), ER (purple), fission site containing filamentous structures perpendicular to the mitochondrial long axis (pale yellow). C) Ciliary transition zone between basal body and axoneme, including assembling IFT train and stellate structure77. Segmented classes: microtubule doublets (light blue), central microtubule pair (light green), stellate structure (pale red), IFT train (yellow). D) Pyrenoid tubule extending from the thylakoids into the phase-separated Rubisco matrix of the pyrenoid. Minitubules originate from thylakoid membranes82. Segmented classes: thylakoid membranes (dark green), PSII (yellow), pyrenoid tubule (lime green), Rubisco (lavender blue), minitubules (orange). Scale bars in A-D: 100 nm. Related to Fig. 2C-H.

To all #TeamTomo #CryoET and #Chlamydomonas aficionados: we have updated EMPIAR-11830 with a bug fix concerning some cryo-CARE denoised tomos as well as additional files and metadata! 🎉👩🏽‍💻

www.ebi.ac.uk/empiar/EMPIA...

A little thread about what's new... 🧵 1/n

Check out the press release about our recent Nature Methods publication on Segment Anything for Microscopy!

Synaptic vesicles segmented with SynapseNet.

Our first deposition of synaptic vesicles segmentations is now in the Cryo ET Portal! We segmented vesicles in over 50 tomograms to enable analysis of membrane proteins and more.
cryoetdataportal.czscience.com/depositions/...

FakET: Simulating cryo-electron tomograms with neural style transfer pubmed.ncbi.nlm.nih.gov/39947174/ #cryoEM

Excited to share that Eugene Khvedchenia and I secured 🏆 1st place out of 950 teams in the CryoET Object Identification Competition hosted by the Chan Zuckerberg Institute for Advanced Biological Imaging (CZII) on Kaggle! www.kaggle.com/competitions...

Hey #teamtomo, if you often find yourself using the excellent membrain-seg from @lorenzlamm.bsky.social et al., you might find my napari plugin "napari-segselect" useful. Let's say your tomogram contains the edges of two bacterial cells, each with a membrane and cell wall:

TomoCPT: a generalizable model for 3D particle detection and localization in cryo-electron tomograms TomoCPT is a generalizable transformer-based 3D particle-picking tool for cryo-tomographic data.

Pranav N. M. Shah et al.: TomoCPT: a generalizable model for 3D particle detection and localization in cryo-electron tomograms #CryoET #ParticlePicking #SubTomogramAveraging @UniofOxford@IEUniversity...#IUCr https://journals.iucr.org/paper?S2059798325000865

And now, support for Zarr v3 & sharding is released as an OME-Zarr specification! 🎉

forum.image.sc/t/ngff-0-5-r...

#NGFF #BioImaging #Formats
@openmicroscopy.org @zarr.dev

Deposition

Here is a direct link to @mgflast.bsky.social's and @thomsharp.bsky.social's deposition: cryoetdataportal.czscience.com/depositions/10314

Exciting update on the CryoET Data Portal! A new annotation set from Mart Last & team is now live. They’ve doubled available annotations with >1,800 tomograms of Chlamydomonas reinhardtii which now have almost fully dense labels, and all can be visualized in the browser using Neuroglancer.

This is a scientific figure from the paper mentioned in the post. It shows fluorescence and electron microscopy images and associated schematics for using the ferritag to image clathrin coated pit proteins.

I'd like to draw your attention to this truly excellent paper from the Taraska lab on cryoET of plasma membrane associated proteins. Everyone who is thinking about probes in the cryoET space should also see what they could do with ferritag (fig 6) www.nature.com/articles/s41...