Genetic Discovery Enabled by A Large Language Model.
Genetic Discovery Enabled by A Large Language Model.
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由大型语言模型实现的基因发现。
DOI：
10.1101/2023.11.09.566468
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Peltz,Gary
中科院分区：
文献类型：
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作者：
Tu,Tao;Fang,Zhouqing;Cheng,Zhuanfen;Spasic,Svetolik;Palepu,Anil;Stankovic,KonstantinaM;Natarajan,Vivek;Peltz,Gary
人工智能 (AI) 已应用于许多医学领域，最近大型语言模型 (LLM) 已显示出临床应用的潜在实用性。然而，由于我们不知道法学硕士的使用是否可以加快基因发现的步伐，因此我们使用小鼠遗传模型生成的数据来研究这种可能性。我们检查了最近开发的专门法学硕士（Med-PaLM 2）是否可以分析通过分析生物医学特征的小鼠模型产生的候选基因组。为了响应自由文本输入，Med-PaLM 2 正确识别了小鼠基因，其中包含经过实验验证的六种生物医学特征的致病遗传因素，其中包括对糖尿病和白内障的易感性。 Med-PaLM 2 还能够分析一系列具有高影响等位基因的基因，这些基因是通过对小鼠基因组序列数据的比较分析来识别的，并确定了导致自发性听力损失的小鼠遗传因素。基于 Med-PaLM 2 的这一发现，开发了一种新的自发性听力损失易感性双基因模型。这些结果表明 Med-PaLM 2 可以分析基因-表型关系并产生新的假设，从而促进基因发现。
Artificial intelligence (AI) has been used in many areas of medicine, and recently large language models (LLMs) have shown potential utility for clinical applications. However, since we do not know if the use of LLMs can accelerate the pace of genetic discovery, we used data generated from mouse genetic models to investigate this possibility. We examined whether a recently developed specialized LLM (Med-PaLM 2) could analyze sets of candidate genes generated from analysis of murine models of biomedical traits. In response to free-text input, Med-PaLM 2 correctly identified the murine genes that contained experimentally verified causative genetic factors for six biomedical traits, which included susceptibility to diabetes and cataracts. Med-PaLM 2 was also able to analyze a list of genes with high impact alleles, which were identified by comparative analysis of murine genomic sequence data, and it identified a causative murine genetic factor for spontaneous hearing loss. Based upon this Med-PaLM 2 finding, a novel bigenic model for susceptibility to spontaneous hearing loss was developed. These results demonstrate Med-PaLM 2 can analyze gene-phenotype relationships and generate novel hypotheses, which can facilitate genetic discovery.