hyperai/awesome-ai4s

What it solves

This project addresses the challenge of keeping track of the rapidly evolving landscape of Artificial Intelligence for Science (AI4S), specifically within the biopharmaceutical and biological research sectors. It serves as a centralized, curated repository of cutting-edge research, models, and algorithms that apply machine learning to complex biological problems.

How it works

The repository acts as a structured bibliography and knowledge base. It categorizes significant recent breakthroughs—ranging from protein design and drug discovery to single-cell analysis and genomic modeling—into a list of specific, high-impact research developments. Each entry highlights a particular tool, framework, or model and summarizes the specific scientific problem it addresses or the performance milestone it achieved.

Who it’s for

This resource is designed for researchers, bioinformaticians, and data scientists working at the intersection of AI and biology. It is particularly useful for those looking to stay updated on state-of-the-art (SOTA) methodologies in drug development, protein engineering, and molecular biology.

Highlights

• Comprehensive list of over 90 AI-driven breakthroughs in biopharmaceuticals and biology.
• Covers diverse topics including protein-protein interaction, de novo protein design, and single-cell multi-omics.
• Features advanced techniques such as diffusion models, graph neural networks, and protein language models.
• Includes links to foundational models and frameworks used for drug discovery, gene mutation prediction, and molecular dynamics simulation.