CryoCloud

@cryocloudio.bsky.social

We provide a cloud-native platform for cryo-EM data analysis which integrates cloud storage, scalable compute and an intuitive web-app for fast and easy end-to-end cryo-EM data analysis.

CryoCloud Map of the Month: TRPV3 in lipid nanodisc We reprocessed EMPIAR-10400 using CryoCloud and achieved: 🚀 3.1 Å resolution (vs. 3.3 Å published) ⚡ 7 compute hours total Curious what your data would look like reprocessed with CryoCloud? 📧 hi@cryocloud.io

🌟 Employee Spotlight: Gydo van Zundert Gydo brings a rare blend of scientific depth and product vision to CryoCloud. He leads our R&D team of scientific software developers, driving the development of novel algorithms and next-generation methods for #cryoEM data analysis. #CryoCloud

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🚀 CryoCloud Webinar Series Cryo-EM datasets are getting larger, but processing them shouldn’t be harder. Join our April webinars on cryo-EM data processing and automated workflows with CryoCloud. 📅 Apr 16 - Academia 📅 Apr 23 - Industry Live demo + Q&A #CryoEM #CryoCloud

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February Map of the Month: Aca2–RNA We reprocessed EMPIAR-11918 and achieved 2.76 Å in 50.5 compute hours. Sub-3 Å at ~40 kDa is a strong example of what modern cryo-EM workflows (and RELION with Blush) can deliver for small targets. 📧 hi@cryocloud.io #CryoEM #CryoCloud

🌟 Employee Spotlight: Thijmen van Buuren Over the past two years, Thijmen has strengthened CryoCloud’s automation workflows, advancing our research infrastructure and scalable data pipelines. As he wraps up his time with us, we thank him for his dedication and impact. All the best, Thijmen! 🚀

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🚀 We’ve launched a new CryoCloud website! CryoCloud has grown significantly over the past few years – more users, more deployments & ongoing technical development across infrastructure and automation. It was time for a website that reflects that evolution. 🌐 Take a look: www.cryocloud.io #cryoEM

🌟 Welcome to the team, Paddy O'Brien! 🇮🇪 We’re thrilled to welcome Paddy as our new Structural Biology Applications AI Intern. Fun fact: Paddy adds another nationality to CryoCloud’s already diverse mix, bringing us to 8 nationalities and counting! 🍀 Welcome aboard, Paddy! 🙌 #CryoCloud #CryoEM

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🔎 Before diving into new 2026 data, we’re looking back at the highlights from the last six months. ⚡️From receptors to kinases and fibrils, each dataset was reprocessed in CryoCloud, often within <2 days, and all resolved to high-quality maps between 2.3 and 3.2 Å. #CryoEM

As 2025 comes to an end, thank you to the CryoCloud community. Every conversation, dataset, and piece of feedback helps us build a better platform for structural biology. From all of us at CryoCloud, wishing you a warm, restful holiday season and a great start to 2026. ✨

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CryoCloud Map of the Month (Holiday Edition 🎄): Alpha‑Synuclein Fibril For December’s edition, we reprocessed EMPIAR‑12229 and generated a 2.3 Å map of the in vitro alpha-synuclein fibril using CryoCloud. 🔬 Dataset size: 5,193 movies 🧠 Compute time: 56.5 hours #CryoEM

🌟 Employee Spotlight: Boy Persoon As Co-Founder and CPO of #CryoCloud, Boy has been the driving force behind turning our ambitious product vision into a functional, user-first platform. If you’ve ever used our platform and thought “this just works” – Boy probably had something to do with it 🍀

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🚨 New blog: GPU-accelerated motion correction Motion correction remains one of the slowest and most costly steps in #cryoEM workflows. So we rebuilt it from scratch. Our new in-house GPU-accelerated CryoCloud Motion Correction is designed for speed, scale and high throughput. lnkd.in/eiJgsYgJ

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🔥 Three years ago, the CryoCloud platform went live 🎉 Today, scientists from 25+ countries rely on it every day for analysing their structural biology data – and we couldn’t be prouder of how far things have come. Thank you to all our users, collaborators, and early supporters 💙 #CryoEM

November Map of the Month: CDK-activating kinase (CAK), an oncology target bound to the covalent inhibitor THZ1 💊 We reprocessed EMPIAR‑11793 and produced a 2.5 Å map of the ~85 kDa CAK-THZ1 complex using CryoCloud. 🔬 Dataset size: 12,572 movies 🧠 Total compute time: 52 hours #CryoEM #CryoCloud