Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, United States.
Department of Health Data Science and Artificial Intelligence, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, United States.
Bioinformatics. 2024 Oct 1;40(10). doi: 10.1093/bioinformatics/btae500.
The vast generation of genetic data poses a significant challenge in efficiently uncovering valuable knowledge. Introducing GENEVIC, an AI-driven chat framework that tackles this challenge by bridging the gap between genetic data generation and biomedical knowledge discovery. Leveraging generative AI, notably ChatGPT, it serves as a biologist's "copilot." It automates the analysis, retrieval, and visualization of customized domain-specific genetic information, and integrates functionalities to generate protein interaction networks, enrich gene sets, and search scientific literature from PubMed, Google Scholar, and arXiv, making it a comprehensive tool for biomedical research. In its pilot phase, GENEVIC is assessed using a curated database that ranks genetic variants associated with Alzheimer's disease, schizophrenia, and cognition, based on their effect weights from the Polygenic Score (PGS) Catalog, thus enabling researchers to prioritize genetic variants in complex diseases. GENEVIC's operation is user-friendly, accessible without any specialized training, secured by Azure OpenAI's HIPAA-compliant infrastructure, and evaluated for its efficacy through real-time query testing. As a prototype, GENEVIC is set to advance genetic research, enabling informed biomedical decisions.
GENEVIC is publicly accessible at https://genevicanath2024.streamlit.app. The underlying code is open-source and available via GitHub at https://github.com/bsml320/GENEVIC.git (also at https://github.com/anath2110/GENEVIC.git).
大量的基因数据的产生对有效挖掘有价值的知识提出了重大挑战。本文引入了 GENEVIC，这是一个由人工智能驱动的聊天框架，通过弥合基因数据生成和生物医学知识发现之间的差距来应对这一挑战。它利用生成式人工智能，特别是 ChatGPT，作为生物学家的“副驾”。它自动分析、检索和可视化定制的特定领域的遗传信息，并集成了生成蛋白质相互作用网络、丰富基因集以及从 PubMed、Google Scholar 和 arXiv 搜索科学文献的功能，是生物医学研究的综合工具。在试点阶段，GENEVIC 使用一个经过整理的数据库进行评估，该数据库根据 Polygenic Score (PGS) Catalog 中的效应权重对与阿尔茨海默病、精神分裂症和认知相关的遗传变异进行排名，从而使研究人员能够优先考虑复杂疾病中的遗传变异。GENEVIC 的操作简单易用，无需任何专门培训即可使用，由 Azure OpenAI 的 HIPAA 合规基础设施提供安全保障，并通过实时查询测试评估其效果。作为原型，GENEVIC 将推进遗传研究，为生物医学决策提供信息支持。
GENEVIC 可在 https://genevicanath2024.streamlit.app 上公开访问。底层代码是开源的，并可通过 GitHub 在 https://github.com/bsml320/GENEVIC.git（也在 https://github.com/anath2110/GENEVIC.git）上获得。
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