554-SpatialAgent: Autonomous AI Discovery in Spatial Biology
The paper introduces SpatialAgent, an autonomous AI agent designed to streamline and enhance research in the field of spatial biology. By utilizing Large Language Models (LLMs) and a specialized toolkit, this system can independently plan, reason, and execute complex workflows such as gene panel design and tissue niche annotation. Benchmarking results demonstrate that the agent frequently outperforms human experts and traditional computational pipelines, especially when identifying biological patterns and predicting spatial coordinates. A key feature of the platform is its hybrid…
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