CRISPR-GPT for Agentic Automation of Gene Editing Experiments

Abstract excerpt

Performing effective gene-editing experiments requires a deep understanding of both the CRISPR technology and the biological system involved. Meanwhile, despite their versatility and promise, Large Language Models (LLMs) often lack domain-specific knowledge and struggle to accurately solve biological design problems. We present CRISPR-GPT, an LLM agent system to automate and enhance CRISPR-based gene-editing desig...

Topics

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• CRISPR-Associated Protein 9
• CRISPR-Cas Systems
• Directed Molecular Evolution
• Gene Editing
• Machine Learning
• Neural Networks, Computer
• Nucleotide Motifs
• Protein Engineering

Identifiers and source

Literature Corpus work

a9527ed3-49d3-5fc8-9fe1-a915b2e95886

DOI

10.1101/2024.04.25.591003