Additional file 1 of Developing neural network diagnostic models and potential drugs based on novel identified immune-related biomarkers for celiac disease

Additional file 1: Table S1. 896 differentially expressed genes. Table S2. Results of three machine algorithms. Table S3. ssGSEA score of 28 immune gene sets in celiac disease patients. Table S4. IG score for GSE11501 training set based on HIGs. Table S5. IG score for GSE164883 validation set based on HIGs. Table S6. ANN diagnosis effect for the grouping of immune characteristics of celiac disease subtypes. Table S7. 2483 immune genes from the ImmPort database. Table S8. 28 immune gene sets from the TISIDB database.

附加文件1：表S1。收录896个差异表达基因。表S2。三种机器学习算法的分析结果。表S3。乳糜泻患者中28个免疫基因集的单样本基因集富集分析（ssGSEA）评分。表S4。基于高免疫基因（HIGs）的GSE11501训练集的免疫基因（IG）评分。表S5。基于高免疫基因（HIGs）的GSE164883验证集的免疫基因（IG）评分。表S6。针对乳糜泻亚型免疫特征分组的人工神经网络（ANN）诊断效能。表S7。来自ImmPort数据库的2483个免疫基因。表S8。来自TISIDB数据库的28个免疫基因集。