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Multimodal generation of protein sequence and all-atom structure using latent diffusion, with compositional function and taxonomic prompts. http://bit.ly/plaid-proteins
FAPLM: A Drop-in Efficient Pytorch Implementation of Protein Language Models
A reactive notebook for Python — run reproducible experiments, execute as a script, deploy as an app, and version with git.
Discovering Interpretable Features in Protein Language Models via Sparse Autoencoders
Benchmarking framework for protein representation learning. Includes a large number of pre-training and downstream task datasets, models and training/task utilities. (ICLR 2024)
Official repository for the Boltz-1 biomolecular interaction model
Bringing bio (molecules and more) to the Hugging Face Datasets library
In silico directed evolution of peptide binders with AlphaFold
Making Protein Design accessible to all via Google Colab!
User friendly and accurate binder design pipeline
From-scratch diffusion model implemented in PyTorch.
High Quality Resources on GPU Programming/Architecture
Structure prediction of alternative protein conformations
The open source frontend for GitBook doc sites
Chai-1, SOTA model for biomolecular structure prediction
Course notes for CS228: Probabilistic Graphical Models.
Versatile computational pipeline for processing protein structure data for deep learning applications.
Open source implementation of AlphaFold3
Resources for the BioML Challenge 2024: Bits to Binders
Pytorch implementation of Transfusion, "Predict the Next Token and Diffuse Images with One Multi-Modal Model", from MetaAI
Joint embedding of protein sequence and structure with discrete and continuous compressions of protein folding model latent spaces. http://bit.ly/cheap-proteins
Bare-bones implementations of some generative models in Jax: diffusion, normalizing flows, consistency models, flow matching, (beta)-VAEs, etc
Sandbox for Deep-Learning based Computational Protein Design
This repository houses all the scripts and notebooks utilized for generating, analyzing, and validating the mdCATH dataset. Some user examples are also available.