从ChatGPT挖掘基因关系的代快速提炼
Yibo Chen1, Jeffrey Gao2, Marius Petruc1
1Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri 65211, USA.
bioRxiv : the preprint server for biology
|January 8, 2024
概括
聊天GPT可以预测基因关系和生物途径,但患有幻觉. 精细的提示显著提高了准确性,使得疾病研究的复杂网络建设成为可能.
科学领域:
- 生物信息学是一种生物信息学.
- 计算生物学 计算生物学
- 人工智能在基因组学中的应用
背景情况:
- 像ChatGPT这样的大型语言模型 (LLM) 显示出提取生物医学信息的前景.
- 一个重大挑战是LLM的"幻觉",导致提取数据中的高假阳性率.
- 准确的基因关系预测对于理解生物途径和疾病机制至关重要.
结论:
- 优化的提示策略可以减轻LLM幻觉,并提高基因关系预测的准确性.
- 可以利用LLM来构建复杂的基因相互作用网络并识别与疾病相关的途径.
- 开发的方法为各种生物信息学预测任务提供了潜在的框架.
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