MOESM1 of Computer-aided prediction of antigen presenting cell modulators for designing peptide-based vaccine adjuvants

Additional file 1: Table S1. Dataset (A-cell epitopes and non-epitope) used for training, testing and validation; including source of information. Table S2. The percent amino acid composition and difference in composition for A-cell epitopes, non-epitopes and human proteins including Students t-test with p-value and adjusted p-value. Table S3. The percent dipeptide composition and difference in composition in A-cell epitopes, non-epitopes and human proteins. Table S4. The percent tripeptide compositions of A-cell epitopes, non-epitopes and human proteins. Rows are sorted in decreasing order of values in the 5th column. Table S5. Motifs exclusively found in A-cell epitopes and their frequency of occurrence, sorted in the decreasing order of counts. Table S6. Motifs exclusively found in non-epitopes and their frequency of occurrence, sorted in decreasing order of counts. Table S7. Performance of various classifiers on the trainingâ testing dataset and the independent dataset. Table S8. The performance of SVM-based A-cell epitope prediction models developed using various features; models were evaluating on training and independent datasets using fivefold cross-validation.

附加文件1：表S1。用于训练、测试与验证的数据集（A细胞表位（A-cell epitopes）与非表位（non-epitopes）），包含信息来源。
表S2：A细胞表位、非表位与人类蛋白质的氨基酸百分组成及组成差异，包含带有p值（p-value）与校正p值（adjusted p-value）的学生t检验（Students t-test）结果。
表S3：A细胞表位、非表位与人类蛋白质的二肽百分组成及组成差异。
表S4：A细胞表位、非表位与人类蛋白质的三肽百分组成。行按照第5列数值的降序排列。
表S5：仅在A细胞表位中发现的基序（motifs）及其出现频率，按计数的降序排列。
表S6：仅在非表位中发现的基序及其出现频率，按计数的降序排列。
表S7：各类分类器在训练、测试数据集与独立数据集上的表现。
表S8：基于各类特征构建的、以支持向量机（Support Vector Machine, SVM）为基础的A细胞表位预测模型的表现；模型通过五折交叉验证（fivefold cross-validation）在训练数据集与独立数据集上完成了评估。