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English(EN) StabilityArc: Decoding Protein Sequence Embeddings into Generalizable Stability Landscapes

StabilityArc 预测蛋白质稳定性图谱,并实现跨蛋白质迁移

研究人员开发了 StabilityArc,一种预测蛋白质稳定性图谱的新方法。该方法使用共享解码器来解释不同蛋白质的生化约束,从而能够更好地预测突变效应。在严格的评估中,StabilityArc 的表现优于现有的零样本基线,并提高了监督模型 Kermut 的准确性。 AI

影响 通过提供更准确的稳定性预测,这项研究有望加速蛋白质工程的实验预筛选。

排序理由 该集群包含一篇详细介绍蛋白质稳定性预测新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

StabilityArc 预测蛋白质稳定性图谱,并实现跨蛋白质迁移

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该集群包含一篇详细介绍蛋白质稳定性预测新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Aaron L. Feller, Andrew D. Ellington, Claus O. Wilke ·

    StabilityArc:将蛋白质序列嵌入解码为可泛化的稳定性景观

    arXiv:2610.00742v1 Announce Type: cross Abstract: Every protein has a unique stability landscape, but the physical consequences of mutation are governed by recurring biochemical constraints. We test whether a shared decoder, trained on measurements from diverse proteins, can inte…