Ai For Science
Showing 8 of 8 projects
A collection of transformer protein language models for predicting structure, function, and designing proteins from sequences.
A family of open-source deep learning models for accurate biomolecular interaction and binding affinity prediction, rivaling AlphaFold3 and physics-based methods.
A state-of-the-art diffusion model for predicting how small molecules (ligands) bind to proteins.
A diffusion framework for controllable protein sequence and evolutionary alignment generation using discrete diffusion models.
High-resolution de novo protein structure prediction from amino acid sequences using deep learning.
Official implementation of a 3D equivariant diffusion model for generating drug-like molecules that bind to specific protein targets and predicting their binding affinity.
A knowledge-informed cross-species foundation model pre-trained on over 120 million human and mouse single-cell transcriptomes to decipher universal gene regulatory mechanisms.
A machine learning approach for rapid, pathologist-level cell type annotation from spatial proteomics data like MIBI and CODEX.
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