Additional file 2 of Integrative multi-omics analysis unveils stemness-associated molecular subtypes in prostate cancer and pan-cancer: prognostic and therapeutic significance

Additional file 2: Data S1. Eighteen stemness signatures for stemness classification. Data S2. Prediction performances of 9- gene stemness subtype predictor based on 100 machine learning algorithms (MLs). Data S3. Details of 100 machine learning algorithms.

附加文件2：数据集S1，包含用于干细胞干性（stemness）分类的18个干性特征标记。数据集S2，包含基于100种机器学习算法（Machine Learning Algorithms，MLs）构建的9基因干性亚型预测器的预测性能。数据集S3，包含100种机器学习算法的详细信息。