category
Nature Genetics
date
Feb 11, 2026
slug
status
Published
summary
创新性地利用转录组数据将未知意义的基因变异分类为超显性、隐性及新功能突变，通过转录因子活性变化和基因表达模式实现功能注释，为精准医疗提供新的突变分型依据。
tags
蛋白质组学
测序技术
type
Post
📄 原文题目
Pan-cancer inference and validation of hypermorphic, hypomorphic and neomorphic mutations
🔗 原文链接
💡 AI 核心解读
创新性地利用转录组数据将未知意义的基因变异分类为超显性、隐性及新功能突变，通过转录因子活性变化和基因表达模式实现功能注释，为精准医疗提供新的突变分型依据。
📝 英文原版摘要
<p>Nature Genetics, Published online: 11 February 2026; <a href="https://www.nature.com/articles/s41588-025-02482-x">doi:10.1038/s41588-025-02482-x</a></p>Protein-activity-based identification of hypermorphic, hypomorphic, neomorphic effectors and therapeutically relevant mutations uses transcriptomic data to categorize variants of unknown significance into hypermorphic, hypomorphic and neomorphic mutations based on their effects on transcription factor activity and subsequent gene expression.
- 作者:NotionNext
- 链接:https://tangly1024.com/article/30548bd6-1f96-8125-87bd-f433cd223d7d
- 声明:本文采用 CC BY-NC-SA 4.0 许可协议，转载请注明出处。
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