(1/16) Nearly two-thirds of ocean carbon fixation flows through a diverse organelle: the pyrenoid. Our new paper maps its 3D architecture in the alga Chlorella and identifies new proteins — expanding the toolkit to engineer this CO2-concentrating machine into crops🧵 #Pyrenoid #CCM #Photosynthesis

It’s a pyrenoid party! 🪩🌍 Awesome collab🤝 of @phaips.vd.st & @manondemulder.bsky.social with Mihris and the @mackinderlab.bsky.social crew to reveal the molecular architecture🏗️ of the Chorella pyrenoid. Algae have so many convergently evolved compartments to supercharge #CO2 capture. #TeamTomo 🔬🌾🌊🧪

Mihris Naduthodi@mihrisn.bsky.social · 2w ago

(1/16) Nearly two-thirds of ocean carbon fixation flows through a diverse organelle: the pyrenoid. Our new paper maps its 3D architecture in the alga Chlorella and identifies new proteins — expanding the toolkit to engineer this CO2-concentrating machine into crops🧵 #Pyrenoid #CCM #Photosynthesis

In #cryoET, separating closely apposed membrane segmentations into distinct labels can be difficult. Small artefacts may connect otherwise separate membranes, requiring tedious slice-by-slice correction. To address this, @jasmred.bsky.social and I developed MemSplit, a napari based workflow.

We're super excited to share MissAlignment: a new ML-based approach to reference-free tilt series alignment, spearheaded by @martenchaillet.bsky.social. We think it's going to make your cryo-ET life a lot better. Preprint: www.biorxiv.org/content/10.6... Code: github.com/warpem/miss-... 🧶 Thread:

Excited to share our paper about copick, a dataset API and toolkit for collaborative annotation and analysis of #cryoET data! Whether you're picking particles or curating segmentations, copick reduces friction and brings #OME-Zarr to cryoET without breaking pipelines. 🧵👇 doi.org/10.1002/pro.70578

Long in the making, but happy to present the Chlamydomonas chlororibosome! Cryo-ET🔬reveals a large new domain on the small subunit, built from multiple extensions in conserved ribosomal proteins. bioRxiv 📖: shorturl.at/q44tG This suggests greater chlororibosome diversity than expected! 1/n 🧵

How does molecular valency shape condensate assembly and function? We used the CO2-fixing organelle in algae—the pyrenoid—to find out… 🧵 Preprint here!: www.biorxiv.org/content/10.6... @cellarchlab.com @phaips.vd.st @biologyatyork.bsky.social #Rubisco #PhaseSeparation #Condensates #Pyrenoid

This one was quite the journey! The paper describing the #ChlamyDataset is finally out and on the cover of Mol Cell! This beautiful rendering made by co-author @jessheebner.bsky.social and Holly Peterson shows an instance of mitochondrial fission found in the dataset 😍 [Maybe long thread ahead]

Toward community-driven visual proteomics with large-scale cryo-electron tomography of Chlamydomonas reinhardtii

Using the latest advances in instrumentation and computational workflows, Kelley et al. present a large-scale annotated cryo-electron tomography dataset of the model green alga, Chlamydomonas reinhard...

cell.com

Molecular Cell @cp-molcell.bsky.social · 7mo ago

The latest issue is now online www.cell.com/molecular-ce...

The #ChlamyDataset is on the cover of @cp-molcell.bsky.social 🖼️🥰! Read @lifeonthewedge.bsky.social's great thread🧵 for the inside scoop🍨 on all the #TeamTomo developments already made possible since these 1829 tomos hit EMPIAR 🧪 🧶🧬 For more, here's the old preprint thread: bsky.app/profile/cell...

Ricardo D. Righetto@lifeonthewedge.bsky.social · 7mo ago

This one was quite the journey! The paper describing the #ChlamyDataset is finally out and on the cover of Mol Cell! This beautiful rendering made by co-author @jessheebner.bsky.social and Holly Peterson shows an instance of mitochondrial fission found in the dataset 😍 [Maybe long thread ahead]

Online Now: Toward community-driven visual proteomics with large-scale cryo-electron tomography of Chlamydomonas reinhardtii Online now:

Toward community-driven visual proteomics with large-scale cryo-electron tomography of Chlamydomonas reinhardtii

Using the latest advances in instrumentation and computational workflows, Kelley et al. present a large-scale annotated cryo-electron tomography dataset of the model green alga, Chlamydomonas reinhardtii. This unprecedented community resource is rich in high-resolution biological information and empowers the development of new methods for visual proteomics.

dlvr.it

In case you're missing my poster at #NeurIPS2025 about how I fine-tuned DINOv2 to ophthalmological images, here are some animations so you don't miss out! 🔗 Preprint: doi.org/10.48550/arX... 🔗 Code: github.com/peng-lab/rmlp 🧵1/9

Are you also often frustrated when DINOv2 puts very high attention on background patches, rather than cute fox heads? @virtualhomo.bsky.social found an elegant way to regularize DINOv2 training using randomised linear algebra 🤯 Check out his thread or even his poster if you're at #NeurIPS2025.

Joel Valdivia Ortega@virtualhomo.bsky.social · 8mo ago

In case you're missing my poster at #NeurIPS2025 about how I fine-tuned DINOv2 to ophthalmological images, here are some animations so you don't miss out! 🔗 Preprint: doi.org/10.48550/arX... 🔗 Code: github.com/peng-lab/rmlp 🧵1/9

I wrote a paper with @lorenzlamm.bsky.social, @marionjasnin.bsky.social, @tingyingpeng.bsky.social, F. Eckardt and B. Schworm and got accepted at #NeurIPS2025 and fun fact: 90% of viewers are enby vegans! 🤟 So if u fit there, u might wanna check it out! Maybe also if you don't. We're allies here <3

Randomized-MLP Regularization Improves Domain Adaptation and Interpretability in DINOv2

Vision Transformers (ViTs), such as DINOv2, achieve strong performance across domains but often repurpose low-informative patch tokens in ways that reduce the interpretability of attention and feature...

arxiv.org

I'm pleased to announce 🍦 Icecream 🍨 v0.3! New features include: * Training on multiple tomograms (same training time, with linear increase in RAM) 🚀 * Logging and plotting of the loss function 📉 * The --scale option is now called --eq-weight for clarity 😉 We'd love to hear your feedback! 🙏🏽

GitHub - swing-research/icecream: 🍦Icecream: a self-supervised framework for cryo-ET reconstruction

🍦Icecream: a self-supervised framework for cryo-ET reconstruction - swing-research/icecream

github.com

Ricardo D. Righetto@lifeonthewedge.bsky.social · 10mo ago

Our colleagues Vinith Kishore and Valentin Debarnot from the @ivandokmanic.bsky.social lab have come up with an amazing deep learning tool for denoising and filling the missing wedge in #cryoET data. I'm pleased to introduce Icecream🍧

You might have noticed lots of activity in the napari project recently! 🚀 We're grateful for a grant from CZI that's keeping us going, but grants don't last forever: we're trying to figure out sustainable long term funding. Read our blog post to find out how you can help: napari.org/island-dispa...

✨Excited that the main project of my PhD is now available as a pre-print on #bioRxiv Here, we used #CryoET to visualise mitochondrial proteostatic stress and together with SPA #CryoEM shed light into the functional cycle of the Hsp60:10 chaperone system. #TeamTomo 🔗 www.biorxiv.org/content/10.1...

Time for a thread!🧵 How different is the molecular organization of thylakoids in “higher” plants🌱? To find out, we teamed up with @profmattjohnson.bsky.social to dive into spinach chloroplasts with #CryoET ❄️🔬. Curious? ..Read on! #TeamTomo #PlantScience 🧪 🧶🧬 🌾 elifesciences.org/articles/105... 1/🧵

🌱 Using ‘compelling’ methods, including #CryoET, researchers mapped spinach thylakoid membranes at single-molecule precision, revealing how photosynthetic complexes are organised and settling long-standing debates on chloroplast architecture. buff.ly/j3TSIkn

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

Proud to share our latest paper. doi.org/10.1016/j.cr... Through the dedication of @glynnca.bsky.social and @cryingem.bsky.social we report a thorough method to image molecular organisation within hippocampus tissue. Structural biology in tissue is well and truly here! @rosfrankinst.bsky.social

Final PhD paper now reviewed and published in JSB:X. I was happy with some great reviews that improved the paper! Thanks to Sander Roet for his help with the code base, and Remco Veltkamp and @fridof.bsky.social

cryoEM papers@cryoempapers.bsky.social · last yr.

pytom-match-pick: A tophat-transform constraint for automated classification in template matching pubmed.ncbi.nlm.nih.gov/40475324/ #cryoEM

We’re kicking off the DinoSphere Online Seminar Series! Join us for our first session with Karel Mockaer (Heidelberg) & Yong Heng Phua (OIST) 📅 1 July 9AM CEST 🔗 tinyurl.com/4mjaverj Spread the word! @protistwtmostest.bsky.social @ehehenberger.bsky.social @chandnibhickta.bsky.social&Norico Yamada

You want to start tomography? Solve structures inside cells? Reach Nyquist 😳 ? @phaips.vd.st and I have a website for you! tomoguide.github.io You'll find a tutorial on how to reconstruct tomograms, pick particles and do subtomogram averaging, using different software! Hope it will be useful !

Philippe Van der Stappen@phaips.vd.st · last yr.

Hey #TeamTomo, Ever been in need of a tutorial about the fundamentals of cryo-electron tomography? From preprocessing raw frames to high-res subtomogram averaging? That's why @florentwaltz.bsky.social and I made this website! tomoguide.github.io Follow the thread 1 /🧵 #CryoET #CryoEM 🔬🧪

Hey #TeamTomo, Ever been in need of a tutorial about the fundamentals of cryo-electron tomography? From preprocessing raw frames to high-res subtomogram averaging? That's why @florentwaltz.bsky.social and I made this website! tomoguide.github.io Follow the thread 1 /🧵 #CryoET #CryoEM 🔬🧪

🚀🔬🦠 Releasing 🤖Cellpose-SAM🤖, a cellular segmentation algorithm with superhuman generalization 🦸‍♀️. Try it now on 🤗 huggingface.co/spaces/mouse... paper: www.biorxiv.org/content/10.1... w/ @computingnature.bsky.social 1/n

MemBrain v2: an end-to-end tool for the analysis of membranes in cryo-electron tomography [updated] Cryo-ET membrane analysis via deep learning.

We’ve updated our powerful MemBrain-seg tool for CryoET membrane segmentation! Plus, we’re introducing two new tools: MemBrain-pick for particle picking and MemBrain-stats for statistical analysis. Feedback is warmly welcome!

Lorenz Lamm@lorenzlamm.bsky.social · last yr.

🦠🧠 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

Check out the latest version of MemBrain, spearheaded by computation superstar @lorenzlamm.bsky.social ! It can segment, pick particles and give you metrics on everything!

Lorenz Lamm@lorenzlamm.bsky.social · last yr.

🦠🧠 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

🦠🧠 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

Yo #TeamTomo, check out our updated #MemBrain v2 preprint. And better yet, give it a whirl on your #CryoET membranes! Please send us your feedback! 🧪🧶🧬🔬

Ricardo D. Righetto@lifeonthewedge.bsky.social · last yr.

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...