Awesome AI-based Protein Design
A curated collection of research papers tracking the frontier of AI-based protein design methods and applications.
What is Awesome AI-based Protein Design?
Awesome AI-based Protein Design is a curated GitHub repository that collects and organizes academic research papers on the application of artificial intelligence to protein engineering. It serves as a living bibliography for scientists and developers, tracking methods like deep generative models, language models, and reinforcement learning for tasks such as de novo protein design, structure prediction, and functional site scaffolding. The project addresses the challenge of staying current with the rapidly advancing intersection of AI and computational biology.
Bioinformatics researchers, computational biologists, AI/ML scientists working in biotech, and graduate students seeking a structured entry point into AI-driven protein design literature.
It provides a centralized, community-updated resource that saves researchers time in literature review, offers structured categorization of complex methodologies, and highlights frontier papers from top-tier journals and conferences that might otherwise be scattered across sources.
Overview
A collection of research papers for AI-based protein design
Use Cases
Best For
- Researchers conducting literature reviews on AI for protein engineering
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