思维图谱生成生物推理的思维过程

ArXiv Pub Date : 2024-03-11 DOI:10.1145/3589335.3651572

Chi-Yang Hsu, Kyle Cox, Jiawei Xu, Zhen Tan, Tianhua Zhai, Mengzhou Hu, Dexter Pratt, Tianlong Chen, Ziniu Hu, Ying Ding

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引用次数: 0

摘要

我们提出了思想图谱（Thought Graph）这一支持复杂推理的新型框架，并以基因组分析为例，揭示了生物过程之间的语义关系。根据与人类注释的余弦相似度，我们的框架在深入理解基因组方面表现突出，比 GSEA 和 LLM 基线分别高出 40.28% 和 5.38%。我们的分析为生物过程命名的未来方向以及对生物信息学和精准医学的影响提供了进一步的见解。

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Thought Graph: Generating Thought Process for Biological Reasoning

We present the Thought Graph as a novel framework to support complex reasoning and use gene set analysis as an example to uncover semantic relationships between biological processes. Our framework stands out for its ability to provide a deeper understanding of gene sets, significantly surpassing GSEA by 40.28% and LLM baselines by 5.38% based on cosine similarity to human annotations. Our analysis further provides insights into future directions of biological processes naming, and implications for bioinformatics and precision medicine.

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ArXiv

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