🔥The 9th Round of Easy Loan, Earn $40 Reward is in progress❗️ ⏰ Promotion Period: January 15th - Feburary 15th, 2025 👉 Register now and check more details at gate.io/campaigns/358

🇨🇭Swiss Secret Sauce? "Common sense and low taxes" according to The Economist. Some mention of EPFL and ETH Zürich also... economist.com/business/2022/…

Our last explorations with MaSIF and surface fingerprints for the computational design of de novo protein-protein interactions ! A lot of hard work from Pablo, @AKVanHall, Sarah, Andrea, Anthony, Michael Bronstein and collaborators biorxiv.org/content/10.110…

MIT offers an excellent course on Deep Learning for Art, Aesthetics, and Creativity. All of the lecture videos are available on YouTube, with a fantastic list of speakers: ali-design.github.io/deepcreativity/

well done @_karlamontse sciencedirect.com/science/articl…

Happy to share our new paper: Structure-based Drug Design with Equivariant Diffusion Models arxiv.org/abs/2210.13695 A demo is available on Google Colab: colab.research.google.com/github/arnesch… 🧵1/6

Today we introduced Chroma, a generative model that creates new proteins & protein complexes given geometric & functional constraints. It learns to transform unstructured, random 3D shapes into #protein molecules, which can have tens of thousands of atoms. ow.ly/Txn750LShFp

Excited to share a preprint outlining a new diffusion model for proteins named Chroma from Generate:Biomedicines! Preprint (will be on biorxiv soon): cdn.generatebiomedicines.com/assets/ingraha… Blog post: generatebiomedicines.com/chroma Some of my favorite highlights in the 🧵 below 1/N

Our new machine learning model, Chroma, can generate extremely large and intricate proteins and #protein complexes in just a few minutes. Read the preprint on bioRxiv and learn about our breakthrough in protein #science: ow.ly/A0oQ50LYIPg #ProteinEngineering

#BundespräsidentCH Alain Berset reist nach Österreich. Er wird in Wien die OSCE besuchen und mit Bundespräsident Alexander Van der Bellen und Bundeskanzler Karl Nehammer u.a. die bilateralen Beziehungen und die Sicherheitslage in Europa thematisieren. 📄admin.ch/gov/de/start/d… (BK)

Nature Biotechnology gives an overview of the use of ML & generative models for protein design, including our model Chroma. Gevorg Grigoryan shares insights about our algorithmic toolbox & how our CryoEM facility is a critical component to developing therapeutics. nature.com/articles/s4158…

Our paper with Bruno Correia Pablo Gainza-Cirauqui et al on protein design using geometric deep learning is finally in @nature We show experimental results of diverse de novo designed binders nature.com/articles/s4158…

New amazing research from the Bruno Correia lab! Zander Bühler Harteveld and Alexandra explore protein topologies that have not been found in nature using a novel deep learning pipeline called Genesis

Dive into the cutting-edge world of generative AI with our CTO & Co-Founder Gevorg Grigoryan in an upcoming episode of @VantAI’s Generative AI in Drug Discovery series. Join Michael Bronstein and Bruno Correia as they gain expert perspective on the role of this technology in drug discovery.

📢 #Call for SNSF Swiss Postdoctoral Fellowships 2024 This highly competitive call is aimed at researchers who wish to obtain a position in a non-profit research institution in Switzerland for a period of 12 to 24 months. 🗓️Deadline: 2 December 2024 sohub.io/6afa

BREAKING NEWS The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in Chemistry with one half to David Baker “for computational protein design” and the other half jointly to Demis Hassabis and John M. Jumper “for protein structure prediction.”

"Exploring ‘'dark-matter' protein folds using deep learning" by EPFL , Imperial College London, Zander Bühler Harteveld, Michael Bronstein, Bruno Correia et al. "... We present a convolutional variational autoencoder that learns patterns of protein structure ..." #deeplearning #proteindesign

Exploring “dark-matter” protein folds using deep learning Cell Systems • Introducing Genesis VAE, a convolutional variational autoencoder that transforms low-resolution protein fold sketches into designable, stable 3D models. • Genesis VAE enables rapid exploration of