DeepNLP-DNA：運用深度編解碼架構及二維卷積神經網路以分析去氧核糖核酸序列表現之預先訓練自然語言處理模型研究(2/2)

This study establishes a novel framework that can improve the interpretation of DNA sequences and the prediction of their molecular functions using transformer NLP + deep learning. The developed framework will be applied in identifying DNA enhancers, promoters, as well as N6-methylation sites that have been proven to be the key mechanisms in molecular biology. This is the first study that observes this combination to improve the predictive performance of DNA bioinformatics research, as well as provides a pre-trained NLP model for general DNA sequences. Through this study, we expect to help transform the world of medicine by training models that predict how genotype defined as a stretch of DNA sequence influences “cell variables”, and enables the exploration of therapies that target these crucial variables.