Giulia Palermo

Giulia Palermo

@giuliapalermo.bsky.social

https://palermolab.com Giulia Palermo Lab at the University of California, Riverside. Biophysicist passionate about Science & Art! In love with Nucleic Acids and Computational Science!

602 followers878 following31 posts

🚀Excited to share our new paper #NatureCommunications 🎉! We uncover a 🧨 #CrypticPocket in #CRISPR #Cas9 that forms transiently on super short timescales not trapped by #cryoEM! 🧬This pocket enables metal ions to regulate #DNA cleavage! 🔗 hhttps://www.nature.com/articles/s41467-026-78458-0

Thrilled to share that I’ll be joining @uclacb.bsky.social as Professor in July 2026! Grateful to my amazing students, postdocs, colleagues @UCR, collaborators, and mentors. A new chapter begins, advancing #compchem, #AI to explore #RNA, #DNA, #CRISPR, and emerging directions in #Biophysics.

The UCLA Department of Chemistry & Biochemistry is excited to welcome world-renowned computational biophysicist Prof. Giulia Palermo, who will join the UCLA faculty as a Full Professor on July 1, 2026! @giuliapalermo.bsky.social www.chemistry.ucla.edu/news/welcomi...

Developed by the multi-talented @pabloarantes.bsky.social & @SouvikSinha members of my lab: ParametrizANI brings #MachineLearning - based #ForceField parametrization available to everyone Available on Github: github.com/palermolab/P...

Pablo Arantes@pabloarantes.bsky.social

🧠💥 ParametrizANI found a home! Our paper is now published in JCIM! Making ML-based force field parametrization open and easy for everyone. With TorchANI, @rdkit.bsky.social & @openmm.org 🔗 pubs.acs.org/doi/abs/10.1... @acs.org @giuliapalermo.bsky.social

New from our lab! 🚀 ParametrizANI - a #NeuralNetworks tool for molecular parametrization. Predicts potential energy surfaces with near-DFT/CC accuracy, at a fraction of the computational cost! #AI #QuantumChemistry #CompChem #ML 🤖 chemrxiv.org/engage/chemr... Try it: github.com/palermolab/P...

github.comGitHub - palermolab/ParametrizANI: ParametrizANI - Fast, Accurate and Free Dihedral Parametrization in the Cloud with TorchANIParametrizANI - Fast, Accurate and Free Dihedral Parametrization in the Cloud with TorchANI - palermolab/ParametrizANI

By leveraging deep learning–based graph representations, our GAT model provides interpretable mechanistic insights from complex molecular simulations and is readily adaptable to a wide range of biological systems.

Thrilled to join #ACSSpring2025 and meet my friends! Don't miss my talk on how #AI & #EnhancedSampling can describe gene editing & refine #cryoEM maps. We’ll be presenting our latest research on #CRISPR-associated transposon systems + other exciting advancements! #compchem #RNA #compchem #RNA

🚀 Exciting new poster from our lab at #BPS2025! 🧬 @Ahsan09966804 showcases how #MolecularDynamics & #AI can enhance #CryoEM map refinement. 📍 Catch it at Board 18 (1824-Pos) today, don’t miss out! #Biophysics #CompBio

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