ImmunoMTL: A Multi-Task Learning Framework for Immunogenicity Prediction

ImmunoMTL is a machine learning framework designed to improve immunogenicity prediction by incorporating MHC-specific preferences. It supports downstream applications such as neoantigen prioritization and immune response modeling.

This repository includes:
• Training and validation data for MMS clustering
• Training and validation data for ImmunoMTL

All datasets were obtained from public resources.

ImmunoMTL是一款机器学习框架，旨在通过整合主要组织相容性复合体（Major Histocompatibility Complex, MHC）特异性偏好以优化免疫原性预测性能。该框架支持新抗原优先级排序与免疫响应建模等下游应用。

本仓库包含以下内容：
• 用于MMS聚类的训练与验证数据集
• 用于ImmunoMTL的训练与验证数据集

所有数据集均来源于公开资源。