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Updated: Jun 16, 2026

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基准测试13种用于突变签名归属的工具,包括一个新的和改进的算法.

Nanhai Jiang1,2, Yang Wu1,2, Steven G Rozen1,2,3

  • 1Centre for Computational Biology, Duke-NUS Medical School, 8 College Road, Singapore 169857, Singapore.

Briefings in bioinformatics
|February 6, 2025
PubMed
概括

基准基准突变特征归属方法揭示了识别癌症突变模式的挑战. 存在属性签名活动 (PASA) 方法显示出希望,但最佳方法选择因癌症类型而异.

关键词:
mSigAct 的使用情况.突变的签名活动活动.突变的签名分析分析.突变的签名归属属性.突变签名暴露的突变签名暴露.软件比较分析软件比较分析

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