We welcome 2022 with our latest publication on Structure, on how the latest advances in AI-driven protein model prediction can help us in the interpretation of complex cryo-EM data from native cell extracts!
We are very excited about the impact of this work, as it is a prime example of how structural biologists can employ advanced AI tools to interpret their data, and how they can avoid any pitfalls during the process.
This work also was the result of a very fruitful collaboration with Grzegorz Chojnowski of EMBL Hamburg, the creator of the findMySequence algorithm as well as one of the main developpers of Arp/Warp!
You can read our publication here:
Cryo-EM and artificial intelligence visualize endogenous protein community members
Congratulations on your publication! Your work on AI-driven protein model prediction for interpreting complex cryo-EM data is groundbreaking. The collaboration with Grzegorz Chojnowski and the integration of advanced algorithms like findMySequence and Arp/Warp highlight the innovative approaches taken. This research is a significant advancement in structural biology. Kudos to you and your team!
Absolutely fascinating! The advancements in cryo-EM combined with AI are truly revolutionary for understanding native cell extracts. It’s incredible to think how far scientific imaging has come. Speaking of detailed images and understanding structures, it reminds me a bit of the intricate designs you find on coloring pages at SSColoring.com – albeit on a vastly different scale of complexity and purpose! This article definitely highlights the exciting future of biological research.
On a completely different, more lighthearted note, for anyone who enjoys detailed and intricate designs, you might find some really cool and complex patterns, perhaps even related to science or nature, on coloring pages at Disegnidacoloraremondo.com. They have a wide variety that could be a fun way to relax after delving into such a dense topic!
Exciting breakthrough! Cryo-EM and AI collaboration enhances understanding of native cell extracts, pushing structural biology to new heights.
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Such a nice article, thanks for sharing this!
This is an excellent demonstration of AI’s role in structural biology, especially in complex cryo-EM data interpretation. The integration of AI-driven tools, like findMySequence, shows promising results. For researchers, even lightweight AI like ChatGPT-o3 Mini, available for free at GPTJP.net, can offer valuable insights during data analysis and hypothesis generation.
You write wonderfully. Thanks for sharing it with us!
How does your recent publication demonstrate the integration of AI-driven protein model prediction with cryo-EM data analysis?
very meaningful article i am also using AI in my work
Fantastic insights! Integrating cryo-EM techniques with AI, as detailed in this article, highlights an exciting future for structural biology research. It reminds me of how tools like ChatGPT Deutsch can similarly enhance data analysis and interpretation, bridging complex computational approaches with practical scientific challenges. Great work—looking forward to seeing further advancements!
This is a fascinating read! The integration of cryo-EM with AI truly opens new doors in structural biology. It’s exciting to see how artificial intelligence is accelerating discoveries at the molecular level. For those interested in AI applications beyond structural analysis, tools like https://gptopenai.fr/ are also helping researchers generate insights, summaries, and technical drafts in multiple languages, including French. Great work—looking forward to more updates from your lab!