Multi-Scale Representation Learning for Protein Fitness Prediction
Designing novel functional proteins crucially depends on accurately modeling their fitness landscape. Given the limited availability of functional annotations from wet-lab …
M²Hub: Unlocking the Potential of Machine Learning for Materials Discovery
We introduce M²Hub, a toolkit for advancing machine learning in materials discovery. Machine learning has achieved remarkable progress in modeling molecular structures, especially …
Geometric Deep Learning for Structure-Based Drug Design: A Survey
Structure-based drug design (SBDD) leverages the three-dimensional geometry of proteins to identify potential drug candidates. Traditional approaches, rooted in physicochemical …