Our review on ML for modeling conformational ensembles is out now in Current Opinion in Structural Biology (w/ @sonyahanson.bsky.social)! It's been exciting to follow all the progress in this field recently, and I'm equally excited to see where it goes!
www.sciencedirect.com/science/arti...
ONE OF THE BIGGEST SHOTS AND CRAZIEST MOMENTS IN CBB HISTORY
THE CONNECTICUT HUSKIES ARE SWEET SIXTEEN BOUND #uconnmbb
#BleedBlue
StrucTTY: An Interactive, Terminal-Native Protein Structure Viewer www.biorxiv.org/content/10.64898/2026.03.17.712308v1 #cryoEM
Annual reminder: if you’ve been accepted to multiple graduate programs and are still deciding, please let the ones you’re definitely not going to know as soon as possible!
-Someone who got into his PhD off the waitlist the day after the deadline
AlphaFold database has entered the era of complexes. Together with NVIDIA, DeepMind and EBI, we use ColabFold, OpenFold and MMseqs2-GPU to predict ~31 million complexes (homo & hetro-dimers) resulting in 1.8 million high-quality predictions
📄 research.nvidia.com/labs/dbr/ass...
🌐 alphafold.ebi.ac.uk
You asked, we listened. Millions of AI-predicted protein complex structures are now available in the #AlphaFold Database.
This spans homodimers from 20 of the most studied species, including humans, as well as the World Health Organization’s priority pathogens list.
www.ebi.ac.uk/about/news/t...
Had a lot of fun working on this with Darius, Christian, and Rohit. We address the problem of unpredictable scaling behavior for PLMs -- with a simple 2-line drop-in replacement for ESM2, you no longer need to worry that a smaller model might end up performing better!
🧵⬇️
We have started a project trying to predic the interactions/structures of all yeast protein pairs using an AlphaFold pooling approach. We are making the current dataset open and we welcome collaborations.
www.evocellnet.com/2026/03/mapp...
Predicting protein-protein interactions (PPIs) at proteome scale can take months with co-folding models due to the massive all-vs-all comparisons required.
We are excited to announce FlashPPI, a contrastive learning framework that predicts proteome wide physical interfaces in minutes. 1/🧵
Additionally, I want to speak directly to Iranian New Yorkers: you are part of the fabric of this city — you are our neighbors, small business owners, students, artists, workers, and community leaders. You will be safe here.
A great start to the Biophysical Society Annual Meeting in San Francisco! Check out the various projects being presented on work from Flatiron Institute people! #bps2026
Introducing The Structural History of Eukarya (SHE): The first proteome-scale phylogeny constructed entirely from 3D structure.
We computed 300 trillion alignments across 1,542 species to map the tree of life. 🧵👇 (1/5)
Looking forward to speaking to @jhucompsci.bsky.social and JHU Biomedical Engineering this Thursday!
FoldMason is out now in @science.org. It generates accurate multiple structure alignments for thousands of protein structures in seconds. Great work by Cameron L. M. Gilchrist and @milot.bsky.social.
📄 www.science.org/doi/10.1126/...
🌐 search.foldseek.com/foldmason
💾 github.com/steineggerla...
Dr Kareem Carr man: i wish to publish @kareem_carr Jan 21 reviewer 2: your paper is no good man: i'll do anything to improve reviewer 2: it's simple. you must read the work of the great scientist Pagliarini man: *bursts into tears* but i am Pagliarini Andre Pagliarini @apagliar Jan 21 a first: in rejecting an article I submitted to a journal, reviewer 2 noted I failed to engage the work of one Andre Pagliarini Jan 21, 2026 • 3:47 PM UTC
I just thought everyone should see this
My time in @martinsteinegger.bsky.social's group is ending, but I’m staying in Korea to build a lab at Sungkyunkwan University School of Medicine. If you or someone you know is interested in molecular machine learning and open-source bioinformatics, please reach out. I am hiring!
mirdita.org
Check our new preprint smoothing rugged Cryo-EM landscapes: shorturl.at/gYs9U
We tackle practical hurdles of Optimal Transport (OT) loss—differentiability, cost & noise sensitivity—make it a feasible inference workhorse.
W/ G. Woollard, D. Herreros, @pilarcossio.bsky.social, K. Dao Duc 🧵👇 (1/9)
🌿 MINT is out now in Nature Communications!
📄: www.nature.com/articles/s41...
💻: github.com/VarunUllanat...
Rockets owners expand talks to buy, move Sun
Terrifying headline if you don’t realize they are sports teams.
The Center for Computational Biology at the Flatiron Institute is accepting applications for summer intern positions. CCB is a great place to work, and the intern program is excellent. Please check out the Computer Vision and Developmental Dynamics groups in particular. apply.interfolio.com/177779
We're recruiting summer interns at all levels (Bachelors, Masters, PhD) and across all groups at @flatironinstitute.org Center for Computational Biology. Come work with us in New York City! (Full-time paid, June 1-August 14 2026, applications close January 16 2026)
apply.interfolio.com/177779
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/challenge #cryoem
**Job Alert** Exciting postdoc position available: theoretical and experimental cryo-EM studies of flexible biomolecules. Competitive salary, collaborative environment at NYSBC and Flatiron Institute. Please share!! and contact: pcossio@flatironinstitute.org
D-SCRIPT + BMPI is out today in Bioinformatics!
academic.oup.com/bioinformati...
Figure 1 from the review. Caption: Comparison of a schematic example showing static, time-dependent, and time-resolved experiments illustrated by a protein folding process. (a) A static experiment measuring the observable O$_{\text{exp}}$ is shown, which can be modelled as a distribution of simulated values, O$_{\text{calc}}$, representing a conformational ensemble of folded and unfolded states. (b) Shows a time-dependent experiment, where the equilibrium dynamics of reversible folding gives rise to measured transition times $\tau_1$ and $\tau_2$. These can be modelled as equilibrium dynamics, illustrated by a free energy (FE) surface along a chosen degree of freedom (D.O.F.) (c) A time-resolved experiment probes a non-equilibrium process, where the system begins at $t_{0}$ in the folded state. During the observation time $t$ the protein unfolds until $t_{\text{max}}$. At each time point, a distinct ensemble average, O$_{\text{exp}}$, can be observed, reflecting the proteins changing structure. This evolution can be modelled as distributions of O$_{\text{calc}}$ at each time point. These are shown together with a FE surface.
Integrative modelling of biomolecular dynamics
Time-dependent and -resolved experiments combined with computation provide a view on molecular dynamics beyond that available from static, ensemble-averaged experiments
Review w @dariagusew.bsky.social & Carl G Henning Hansen
doi.org/10.48550/arX...
These are the quarterbacks since 2010 who complete passes at roughly the rate Microsoft Excel’s AI mode accurately edits spreadsheets
