Training Nmers randomly subsampled to reduce expression bias

Mutated Nmers from the balanced training set described in the manuscript titled "A machine learning model for ranking candidate HLA class I neoantigens based on known neoepitopes from multiple human tumor types". These Nmers have been randomly selected to reduce the expression bias in the data amongst the screened nmers本数据集所采用的突变型N聚体（Mutated Nmers）取自标题为《基于多种人类肿瘤类型已知新表位的候选人类白细胞抗原I类新抗原排序机器学习模型》的研究手稿中描述的平衡训练集。上述N聚体均经随机选取，以降低经筛选的N聚体数据集中的表达偏倚。