Thought Graph: Generating Thought Process for Biological Reasoning
arXiv:2403.07144 · doi:10.1145/3589335.3651572
Abstract
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.
arXiv comment4 pages. Accepted by Web Conf 2024