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AI2 Asta: Accelerating Research
This talk details using AI2's Asta agents for an iterative genomics target selection pipeline, streamlining literature extraction and accelerating research discovery.
Using AI2’s Asta Agents/MCP to streamline scientific literature extraction, enhancing throughput for laboratory applications. I’ll briefly discuss the project I’m working on as a student researcher at Seattle Children’s, an agentic AI genomics target selection pipeline that finds promising drug targets proposed in literature and flags them for study. It uses Asta agents to perform the iterative literature search, as finding promising papers necessitates self-reflection, changing queries, and dynamic analysis, which would be difficult without Asta agents.
I will discuss how I implemented this workflow, show how it runs, and discuss its performance with some open-source LLMs.
I’ll also mention how implementing this same workflow from scratch in June with PydanticAI was a complete pain and Asta simplified it by leaps and bounds.
Main message: It’s great how a student researcher like myself can have access to these amazing tools and have an actual impact. LLMs will only become more accessible from here, which is cool.