Finding Potential Pathways of Atopic Dermatitis for Drug Targetingby Visualizing Gene Expression Over Time

Current methods for targeting the skin condition atopicdermatitis are inconvenient due to high costs andinconsistency, complicating their use in clinical practice.The aim of this study is to develop a machine learningmodel that utilizes microRNAs as biomarkers to improvethe precision of targeting genes involved in atopicdermatitis treatment. To achieve this, the study employeda range of online databases, machine learning tools, anddata processing tools, including NCBI, miRBase, miRDB,and Weka to organize and analyze relevant data.

目前针对特应性皮炎这一皮肤疾病的靶向治疗方法因成本高昂且效果不稳定而存在不便，使其在临床实践中的应用较为复杂。本研究旨在开发一种机器学习模型，该模型以微小核糖核酸（microRNAs）作为生物标志物（biomarkers），以提高特应性皮炎治疗中相关靶向基因的精准度。为实现这一目标，本研究采用了一系列在线数据库、机器学习工具及数据处理工具，包括NCBI、miRBase、miRDB和Weka，对相关数据进行组织与分析。