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Reposted by Utz Ermel

The BioImage Archive @bioimagearchive.bsky.social · 23d

🎉 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

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Kyle Harrington @kyleharrington.com · Aug 26

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...

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...

doi.org

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SBGrid Consortium @sbgrid.bsky.social · Aug 14

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

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.

buff.ly

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Lorenz Lamm @lorenzlamm.bsky.social · Apr 25

🦠🧠 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

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Ricardo D. Righetto @lifeonthewedge.bsky.social · Apr 23

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...

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.

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Sergio Cruz-León @sergiocruzleon.bsky.social · Apr 11

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

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Florent Waltz @florentwaltz.bsky.social · Mar 21

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.

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Kaggle @kaggle.com · Mar 6

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

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

BYU - Locating Bacterial Flagellar Motors 2025

Help locate flagellar motors in three-dimensional reconstructions of bacteria.

kaggle.com

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Utz Ermel @uermel.bsky.social · Mar 6

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!

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Utz Ermel @uermel.bsky.social · Mar 6

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/...

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

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Utz Ermel @uermel.bsky.social · Mar 6

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

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Sven Klumpe @svenklumpe.bsky.social · Mar 5

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?

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Utz Ermel @uermel.bsky.social · Feb 28

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

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Ricardo D. Righetto @lifeonthewedge.bsky.social · Feb 28

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

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.

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Constantin Pape @cppape.bsky.social · Feb 24

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

Uni Göttingen @uni-goettingen.de · Feb 24

Automatic cell analysis using #AI

Researchers retrained existing AI-based software on over 17,000 microscopy images with over 2 million structures to develop this new model - Segment Anything for Microscopy: www.uni-goettingen.de/en/3240.html...

#NatureMethods research: doi.org/10.1038/s415...

This is a flat grey image with cell structures in darker grey. Some of the cells are coloured and shown in green boxes. This image - Segmentation of electron microscopy images with μSAM - shows how the model can segment nuclei, with points and boxes from the user and the corresponding masks predicted by the model.
Photo: The underlying image comes from data published in Cell (S0092-8674(21)00876-X). Image created by Anwai Archit using the μSAM tool.

This is a three dimensional representation with a cross-section showing dark patches in different colours and the outside of the structure with bright different colours (green, purple, blue, dark pink, yellow, orange). The image shows plant cells acquired with a fluorescence microscope that were segmented automatically with the model. The underlying data is three-dimensional and the image shows a rendering of the segmented cells, each represented by a different colour.
Image from: Nature Methods: s41592-021-01249-6

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Constantin Pape @cppape.bsky.social · Feb 21

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/...

Synaptic vesicles segmented with SynapseNet.

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cryoEM papers @cryoempapers.bsky.social · Feb 14

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

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Dieter @kagglingdieter.bsky.social · Feb 7

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...

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Benedikt Wimmer @bwmr.net · Feb 6

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:

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Structural Biology @actacrystd.iucr.org · Feb 5

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...##IUCrhttps://journals.iucr.org/paper?S2059798325000865

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.

journals.iucr.org

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Josh Moore @joshmoore.bsky.social · Jan 28

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

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Utz Ermel @uermel.bsky.social · Jan 23

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

Deposition

cryoetdataportal.czscience.com

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Bridget Carragher @bcarra.bsky.social · Jan 23

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.

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Rita Strack @ritastrack.bsky.social · Jan 22

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...

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.

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Max Planck Institute of Biophysics @mpibp.bsky.social · Jan 17

Fresh out of the press! ✨Check out our new paper on the violent entry of the HIV capsid into the nuclear pore — and how it cracks the gate! 🤯 💥 Incredible work from @becklab.bsky.social and @hummerlab.bsky.social 🤩 More here: www.biophys.mpg.de/2842024/hivcapsid-cracks-the-npc?c=2011019 🔗 #teamTOMO

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