Thought Graph: Generating Thought Process for Biological Reasoning
Chi-Yang Hsu Kyle Cox Jiawei Xu Zhen Tan Tianhua Zhai Mengzhou Hu Dexter Pratt Tianlong Chen Ziniu Hu Ying Ding
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.