Future-House/BixBench
Benchmark for LLM-based Agents in Computational Biology
This project provides a standardized way to test how well AI agents can handle real-world computational biology tasks. It takes in an AI agent and a set of bioinformatics problems, then outputs a performance evaluation, showing how accurately the agent can explore datasets, perform multi-step analyses, and interpret results. This is useful for researchers and developers working on AI agents for biological research.
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Use this if you are developing or evaluating AI agents designed to solve complex problems in bioinformatics and want to rigorously benchmark their capabilities against a diverse set of real-world scenarios.
Not ideal if you are looking for a tool to directly perform bioinformatics analyses or develop new biological models, as this is a benchmarking framework, not an analysis tool.
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Language
Python
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Apache-2.0
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Last pushed
Oct 06, 2025
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