{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"萌喵读文献-生物信息学","title":"今日生物信息学最高分文献 - 2026-03-16","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/71fd3b75\"></iframe>","width":"100%","height":180,"duration":172,"description":"科研喵使用ai读文献，祝你效率百倍，访问labcat.com.cn下载。\n\n本期关注一篇发表在《Briefings in bioinformatics》(IF: 6.8)上的重要研究《Decoding TCR recognition via geometric deep learning of immunological fingerprints》。该研究创新性地引入了多模态几何深度学习框架，成功解码了T细胞受体(TCR)识别肽-主要组织相容性复合物(pMHC)分子的机制。研究团队从pMHC界面提取关键特征，不仅能够预测TCR结合偏好，还揭示了受体识别的\"免疫学指纹\"。更令人振奋的是，该模型发现了自身肽与细菌肽间潜在的TCR交叉反应性，为理解分子模拟提供了新视角。这一突破性进展为抗原设计、疫苗开发和TCR为基础的免疫疗法开辟了全新途径，有望彻底改变我们对抗疾病的方式。","thumbnail_url":"https://img.transistorcdn.com/38WU46uKrju37cyiLrKcVSktFL4vxBb_oTgbpM_2CRw/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8zOGU2/ZmEyYWE0MDZkNGFj/NWMzNGY5ZmU4YTk0/ZTBlNS5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}