Published May 13, 2024
| Version Published
Conference Paper
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Thought Graph: Generating Thought Process for Biological Reasoning
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. Here’s our Github Code.
Copyright and License
© 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.
Acknowledgement
We thank the support from NIH (OTA-21-008, R01LM014306-01) and NSF (NSF 2303038, NSF 2333703).
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Additional details
Funding
- National Institutes of Health
- OTA-21-008
- National Institutes of Health
- R01LM014306-01
- National Science Foundation
- IIS-2303038
- National Science Foundation
- ITE-2333703