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超越序列:一个基于物理的机器学习框架,用于预测DNA突变

M Suárez-Villagrán1, N Mitsakos2, J H Miller1

  • 1Department of Physics and Texas Center for Superconductivity, University of Houston, Houston, TX 77204, USA.

Computational and structural biotechnology journal
|September 29, 2025
PubMed
概括

机器学习模型可以通过使用量子紧结模型更好地预测线粒体DNA (mtDNA) 中易发生突变的位点. 这种方法分析基对能量和电子相互作用,改善突变位点识别,特别是在同聚合物运行中.

关键词:
它们是DNA DNA DNA DNA.同聚合物运行是同聚合物运行.超变区1 超变区1 超变区机器学习 机器学习线粒体DNA是线粒体的DNA.突变 突变 突变 突变 突变量子生物学就是量子生物学.

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