pMTnet_omni_cytokine.csv

pMTnet-omni is deep contrastive learning model based on hybrid protein sequence and structure information, to predict the pairing of TCRs of αβ T cells with peptide-MHC complexes (pMHCs).This dataset is the cytokine data we used in the pMTnet-omni paper when developing a biomarker for predicting irAEs. As there are some duplicated sample ids, we recommend taking averages within each sample id.<br>

pMTnet-omni是一款基于混合蛋白质序列与结构信息的深度对比学习模型，旨在预测αβ T细胞的T细胞受体（TCR (T-cell receptor)）与肽-主要组织相容性复合体复合物（pMHCs）的配对相互作用。本数据集为我们在pMTnet-omni论文中开发预测免疫相关不良反应（irAEs (immune-related adverse events)）的生物标志物时所使用的细胞因子数据集。由于存在部分重复的样本ID，我们建议对每个样本ID内的数据取平均值。