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English(EN) ENSEMBITS: an alphabet of protein conformational ensembles

新型Ensembits分词器捕捉蛋白质动力学用于语言建模

研究人员开发了Ensembits,这是一种新颖的分词器,旨在表示蛋白质构象集合,它捕捉了超越静态结构的动态运动和替代状态。这种新方法通过使用具有帧蒸馏目标的残差VQ-VAE来解决编码可变大小集合和稀疏动力学数据的挑战。Ensembits在预测蛋白质动力学方面表现出优越的性能,并且在各种预测任务上匹配或超过静态分词器,尽管使用了更少预训练数据,为将动力学纳入蛋白质语言建模和设计铺平了道路。 AI

影响 能够将蛋白质动力学纳入语言模型,推进蛋白质设计和分析。

排序理由 该集群包含一篇详细介绍新型蛋白质构象集合分词方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新型Ensembits分词器捕捉蛋白质动力学用于语言建模

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该集群包含一篇详细介绍新型蛋白质构象集合分词方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Carlos Oliver ·

    ENSEMBITS:蛋白质构象集合的字母表

    Protein structure tokenizers (PSTs) are workhorses in protein language modeling, function prediction, and evolutionary analysis. However, existing PSTs only capture local geometry of static structures, and miss the correlated motions and alternative conformational states revealed…