Supplementary files for the article "Inverse Similarity and Reliable Negative Samples for Drug Side-effect Prediction"

Supplementary file 1: The supplementary figures for this work. Figure S1: Scatter plots of F1-scores for different classifiers using ChemTar similarity on balanced and unbalanced dataset. Figure S2: Scatter plots of F1-scores for ComNegative and ChemTarRandom using different classifiers. Supplementary file 2: The supplementary tables for this work. Table S1: List of 917 drugs studied in this work. Drug names, drug target proteins, substituents of drugs, ATC codes and the SMILES strings are included as well. Table S2: List of 500 side-effect terms studied in this work. Table S3: F1-scores of different similarity measurements and different similarity integration methods using KNN. Table S4: F1-scores of different classifiers using the comprehensive similarity on balanced and unbalanced training sets. Table S5: F1-scores of different classifiers using the proposed negative sample selection method and random sample selection method.补充材料1：本研究的补充图表。图S1：采用ChemTar相似度，在平衡与非平衡数据集上不同分类器的F1值散点图。图S2：采用不同分类器时，ComNegative与ChemTarRandom的F1值散点图。补充材料2：本研究的补充表格。表S1：本研究涉及的917种药物列表，其中涵盖药物名称、药物靶蛋白、药物取代基、ATC编码（ATC codes）以及SMILES字符串（SMILES strings）。表S2：本研究涉及的500个副作用术语列表。表S3：采用K近邻（KNN）时，不同相似度度量方式与不同相似度融合方法的F1值。表S4：在平衡与非平衡训练集上，采用综合相似度时不同分类器的F1值。表S5：采用本文提出的负样本选择方法与随机样本选择方法时，不同分类器的F1值。