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Published Date : 29/07/2025
Researchers at the National Institutes of Health (NIH) have developed an AI agent, GeneAgent, that enhances the accuracy of gene set analysis by cross-checking its predictions against expert-curated databases.
Researchers at the National Institutes of Health (NIH) have developed an AI agent, GeneAgent, that enhances the accuracy of gene set analysis by cross-checking its predictions against expert-curated databases.
Researchers at the National Institutes of Health (NIH) have developed an artificial intelligence (AI) agent called GeneAgent, which significantly improves the accuracy and reliability of gene set analysis. GeneAgent leverages a large language model (LLM) to create more accurate and informative descriptions of biological processes and their functions.
GeneAgent stands out by cross-checking its initial predictions, or claims, against information from established, expert-curated databases. This verification process helps researchers interpret high-throughput molecular data and identify relevant biological pathways or functional modules, leading to a better understanding of how different diseases and conditions affect groups of genes.
AI-generated content, produced by LLMs trained on vast amounts of text data, can sometimes be false, misleading, or fabricated, a phenomenon known as AI hallucinations. Additionally, LLMs are prone to circular reasoning, which can make them sound more confident in their output even when the information is incorrect. GeneAgent mitigates these issues by independently comparing its claims to established knowledge in external databases.
The research team tested GeneAgent on 1,106 gene sets sourced from existing databases with known functions and process names. For each gene set, GeneAgent generated an initial list of functional claims and then used its self-verification module to cross-check these claims against the curated databases. A verification report was created, noting whether each claim was supported, partially supported, or refuted.
To evaluate the accuracy of the self-verification step, two human experts manually reviewed 10 randomly selected gene sets with a cumulative 132 claims. The experts determined that 92% of GeneAgent’s self-verification reports were correct, indicating high performance in its ability to conduct self-verification. This is particularly significant when compared to other models like GPT-4, which do not have the same level of verification capability.
The research team also applied GeneAgent to real-world scenarios, using it on seven novel gene sets derived from mouse melanoma cell lines. GeneAgent provided valuable insights into novel functionalities for specific genes, which could lead to the discovery of potential new drug targets for diseases like cancer.
While LLMs like GeneAgent are still limited by the information they can use and their inability to reason as humans, GeneAgent’s ability for self-driven fact-checking shows remarkable promise in mitigating AI hallucinations. This could have significant implications for advancing medical research and improving the accuracy of gene set analysis.
About the National Library of Medicine (NLM): NLM is a leader in research in biomedical informatics and data science and is the world’s largest biomedical library. NLM conducts and supports research in methods for recording, storing, retrieving, preserving, and communicating health information. It creates resources and tools that are used billions of times each year by millions of people to access and analyze molecular biology, biotechnology, toxicology, environmental health, and health services information. Additional information is available at https://www.nlm.nih.gov/.
About the National Institutes of Health (NIH): NIH, the nation's medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit https://www.nih.gov/. NIH…Turning Discovery Into Health®.
Frequently Asked Questions (FAQS):
Frequently Asked Questions (FAQS):
Q: What is GeneAgent?
A: GeneAgent is an AI agent developed by the National Institutes of Health (NIH) that enhances the accuracy of gene set analysis by cross-checking its predictions against expert-curated databases.
Q: How does GeneAgent improve gene set analysis?
A: GeneAgent improves gene set analysis by generating more accurate and informative descriptions of biological processes and functions. It cross-checks its claims against established, expert-curated databases to verify the accuracy of its predictions.
Q: What is the significance of self-verification in GeneAgent?
A: Self-verification is significant in GeneAgent because it helps mitigate AI hallucinations and circular reasoning, ensuring that the generated content is more reliable and accurate.
Q: How was GeneAgent tested?
A: GeneAgent was tested on 1,106 gene sets with known functions and process names. It generated initial claims and then cross-checked them against curated databases. Human experts also reviewed a subset of the results to evaluate the accuracy of the self-verification process.
Q: What are the potential real-world applications of GeneAgent?
A: GeneAgent can provide valuable insights into novel functionalities for specific genes, which could lead to the discovery of potential new drug targets for diseases like cancer.
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