AI-Driven Drug Repurposing through miRNA-mRNA Relation
Sharanya Manoharan, Balu Bhasuran, Oviya Ramalakshmi Iyyappan, Mohamed Saleem Abdul Shukkoor, Malathi Sellapan, Kalpana Raja
miRNA mRNA关系与几个生物过程和疾病机制密切相关 在最近的一项研究中,我们测试了大型语言模型LLMs在从PubMed PubMedBERT提取miRNA mRNA关系方面的表现,为miRNA mRNA相互作用Corpus MMIC取得了0.783 F1评分的最佳表现 在这里,我们首先应用了微调的PubMedBMT模型,从PubMed中提取miRNA mRNA关系。我们使用KinderMiner检索了miRNA药物关系,这是一种用于关系提取的文献挖掘工具,然后我们构建了三个相互作用网络1个疾病中心网络2个以药物为中心的网络和3个miRNA中心网络,由3497个节点和16417个边缘组织为捕获复杂的生物关系,最后我们验证了使用MIMIC IV的药物,我们的综合方法揭示了通过从PubMed中提取的595 miRNA药物关系,为研究的疾病建立了和新颖的候选药物。
miRNA mRNA relations are closely linked to several biological processes and disease mechanisms In a recent study we tested the performance of large language models LLMs on extracting miRNA mRNA relations from PubMed PubMedBERT achieved the best performance of 0.783 F1 score for miRNA mRNA Interaction Corpus MMIC Here we first applied the finetuned PubMedBERT model to extract miRNA mRNA relations from PubMed for chronic obstructive pulmonary disease COPD Alzheimers disease AD stroke type 2 diabet...
