Ryan Feathers
@FeathersRyan
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Postdoc @Princeton | PhD @Cornell | @okstate alum | Interested in studying mechanisms of membrane trafficking using cryo-EM
Princeton, NJ
Joined October 2018
I'm so excited to finally share the results of my PhD work! Check out this thread for all of the highlights! Ric1-Rgp1-Rab6 has been the most difficult #cryoEM project I've worked on so far, but I'm so happy with how it came together and what we learned about Rab6 activation!
We are excited to share a new preprint from the lab! Rab6 is a central regulator of the Golgi, important for trafficking and autophagy. @FeathersRyan used #cryoEM to determine the structural basis of the Rab6 activation process. (1/9)
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We’ll be presenting CryoBoltz ❄️⚡️ at #NeurIPS this week! Check out the new experiments in our updated paper. We’re also releasing our code for the community to try out on their data 🚀 Paper: https://t.co/rPMtaPLUR7 Code:
github.com
CryoBoltz code for protein structure prediction with cryo-EM guidance. NeurIPS 2025. - ml-struct-bio/cryoboltz
Excited to present CryoBoltz ❄️⚡, a multiscale guidance approach for steering AlphaFold3/Boltz-1 to sample structures that are consistent with experimental cryo-EM density maps. 🧵1/7 https://t.co/rPMtaPMsGF Joint work with @axlevy0 @GordonWetzstein & @ZhongingAlong!
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Reviewed a nice #CryoET paper in journal club today and it got me wondering... @ScienceMagazine has a very clear policy on data and computational methods. Why isn't this policy upheld for the #CryoEM and #TeamTomo communities? #OpenSoftwareAcceleratesScience
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Calling all #CryoEM aficionados and method developers! Come join the webinar happening soon to learn more about our new community data processing challenge! #CAHRA
If you're not on the multi-thousand-person cryo-EM listservs... we (EZ lab @PrincetonCS, @FlatironInst, #CCPEM) just announced a new #heterogeneity challenge for cryo-EM! #CAHRA2025 Webinar this Fri Nov 14 at 12p ET. Datasets and more info here: https://t.co/2wEVkObp8x We've
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If you're not on the multi-thousand-person cryo-EM listservs... we (EZ lab @PrincetonCS, @FlatironInst, #CCPEM) just announced a new #heterogeneity challenge for cryo-EM! #CAHRA2025 Webinar this Fri Nov 14 at 12p ET. Datasets and more info here: https://t.co/2wEVkObp8x We've
heterogeneity.notion.site
A community-wide data processing challenge for cryo-electron microscopy.
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Announcing cryo-EM heterogeneity challenge #2, now dubbed the 2025 Community-Wide Assessment of Cryo-EM Heterogeneous Reconstruction Algorithms (CAHRA)! Join us for a webinar next Friday (Nov 14th) to learn more. Datasets already posted here:
heterogeneity.notion.site
A community-wide data processing challenge for cryo-electron microscopy.
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Congratulations to @tri_dao and @ZhongingAlong on being named AI2050 Early Career Fellows by @schmidtsciences! The AI2050 fellowships fund researchers working to solve hard problems in AI and improve technology for the benefit of humanity by 2050. https://t.co/FSNfP2YFtE
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new podcast filmed with someone who basically created a new subfield in bio-ml during her phd, and whose lab at Princeton continues to remain at the forefront of the field out (hopefully) next weekend to prepare, you should read the article below
A primer on ML in cryo-electron microscopy (cryo-EM) https://t.co/YXSfbIdTrz confused about cryo-EM??? i explain why people do it, how it works and some ML problems in the area via explanations of 3 @ZhongingAlong papers 7.9k words, 36 minutes reading time. ToC in thread❄️
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Congrats Scott for his discovery of ESCRTs.
The 2025 WLA Prize in Intelligent Science or Mathematics was awarded to Richard Schoen, honorary chair professor at Stanford University's School of Humanities and Sciences, CCTV reported today. The prize in Life Sciences or Medicine was awarded to Scott D. Emr, honorary professor
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CryoDRGN-AI ❄️🐉🤖 is now published in @naturemethods!!! So excited to see this out and a huge congrats to @axlevy0 and team! CryoDRGN-AI extends cryoDRGN from requiring input, fixed camera poses, to end-to-end ab initio reconstruction of biomolecules and their conformational
We present DRGN-AI for fast, ab initio cryo-EM reconstruction! * learns a neural field from unposed images, * designed for single-shot reconstruction of unfiltered datasets, * finds new states missed by prior approaches! Teamwork led by @ZhongingAlong
https://t.co/WjPStRkrnI 1/
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🎉New preprint!🎉 Extremely excited to share CryoBoltz❄️⚡️, led by superstar @rishwanth_raghu! We develop a multiscale guidance recipe to steer structure prediction models (e.g. AlphaFold3 / Boltz-1) towards experimental cryo-EM density maps, including heterogeneous,
Excited to present CryoBoltz ❄️⚡, a multiscale guidance approach for steering AlphaFold3/Boltz-1 to sample structures that are consistent with experimental cryo-EM density maps. 🧵1/7 https://t.co/rPMtaPMsGF Joint work with @axlevy0 @GordonWetzstein & @ZhongingAlong!
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🚀 Exciting update on CryoBench! 🚀 We’ve refactored the metric (per-img-FSC) script to make it even easier to use and created a user manual on GitBook: CryoBench Manual: https://t.co/RljyMN5akO Big thanks to Michal Grzadkowski for the amazing refactor! 🙏
ez-lab.gitbook.io
Datasets, metrics, and performance benchmarks for heterogeneous reconstruction in cryo-EM
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🚨New paper at #NeurIPS2024! We present Hydra, a mixture of neural fields 🐉🐉🐉 for ab initio cryo-EM reconstruction of complex mixtures. Hydra is our attempt at pushing the boundaries for even more extreme forms of heterogeneity in cryo-EM 🤯. This was joint work with an
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CryoBench 🧊🪑is accepted at NeurIPS as a Spotlight! Poster session happening now! @MinkyuJeon19791 We’ve been making a lot of improvements to the code and docs to make it as easy as possible to compute metrics ➡️ https://t.co/2waQqk8i78 The heterogeneity problem in cryo-EM is
ez-lab.gitbook.io
Datasets, metrics, and performance benchmarks for heterogeneous reconstruction in cryo-EM
Excited to share CryoBench🧊🪑 our dataset and benchmarking effort for heterogeneous cryo-EM reconstruction! Led by @MinkyuJeon19791, who is an absolute machine, and super fun collab with @PilarCossio2 @sonyahans groups @FlatironInst A few thoughts on our benchmark design 👇
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@Fromme_Lab use cryo-electron microscopy and functional experiments to reveal how Rab6 is activated by the Ric1-Rgp1 complex. https://t.co/9a6vwvopp1
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These are exciting times for #TeamTomo and I think the best is yet to come! I'm so grateful for the opportunity to work in such supportive and collaborative groups in @PrincetonMolBio and @PrincetonCS 👨🔬👨💻
Belated, but super proud of @FeathersRyan for winning a talk award at @PrincetonMolBio retreat on our work visualizing heterogeneous structures inside cells with cryoDRGN-ET! ❄️🐉🗡️ And I'm omw to give a talk about this work led by @ramyarangan and Ryan at #SSP2024 in Boston!
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You can find cryoDRGN-ET along with many new features and improvements in the latest version of the cryoDRGN ❄️🐉 software (v3.4.1). V3.4.2 release coming in hot by @MGrzadkows26472 later this week 🔥
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Some thoughts on the current state of single particle cryo-EM map/model validation. (TLDR: preferred orientation remains a big problem, ❤️ Q-scores. There's been progress, but there's still more to do. ) https://t.co/E3jcBOyeKA
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🚀 Excited to share our preprint: CryoBench 🧊🪑: Diverse & Challenging Datasets for the Heterogeneity Problem in Cryo-EM! 🌐 https://t.co/qssgR7hlWd 🙌 Huge thanks to my amazing co-authors, collaborators, & advisor @zhongingalong! 🎉 #cryoEM #MachineLearning 🧵 Details below!
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Excited to share CryoBench🧊🪑 our dataset and benchmarking effort for heterogeneous cryo-EM reconstruction! Led by @MinkyuJeon19791, who is an absolute machine, and super fun collab with @PilarCossio2 @sonyahans groups @FlatironInst A few thoughts on our benchmark design 👇
🚀 Excited to share our preprint: CryoBench 🧊🪑: Diverse & Challenging Datasets for the Heterogeneity Problem in Cryo-EM! 🌐 https://t.co/qssgR7hlWd 🙌 Huge thanks to my amazing co-authors, collaborators, & advisor @zhongingalong! 🎉 #cryoEM #MachineLearning 🧵 Details below!
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Awesome to see our work on cryoDRGN-ET is now out in @naturemethods! CryoDRGN-ET can resolve the structural heterogeneity of macromolecules in situ from cryo-ET data. We've showcased the method here on ribosomes and yeast fatty acid synthase.
CryoDRGN-ET❄️🐉 is published in @naturemethods! We combine neural fields and generative modeling to reveal the structural heterogeneity of protein complexes *in situ*! So excited to see this out, and huge congrats to @ramyarangan, @FeathersRyan and team! https://t.co/4l8G2D315h
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