Process / pipelineBioinformatics / omics
机器学习辅助序列比对
机器学习辅助序列比对使用统计学习模型——包括深度神经网络和蛋白质语言模型——来计算核苷酸或氨基酸序列之间具有生物学意义的比对。通过从大型训练语料库中学习取代模式和结构约束，这些方法在远程同源序列和结构约束区域的敏感性方面超越了经典的评分矩阵（例如，BLOSUM、PAM），使其成为基因组学和蛋白质组学中困难比对任务的当前最先进技术。
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来源
- Llinares-López, F., Berthet, Q., Blondel, M., Teboul, O., & Vert, J.-P. (2023). Deep embedding and alignment of protein sequences. Nature Methods, 20(1), 104–111. DOI: 10.1038/s41592-022-01700-2 ↗
- Jumper, J., Evans, R., Pritzel, A., et al. (2021). Highly accurate protein structure prediction with AlphaFold. Nature, 596(7873), 583–589. DOI: 10.1038/s41586-021-03819-2 ↗
如何引用本页
ScholarGate. (2026, June 3). Machine Learning-Assisted Sequence Alignment. ScholarGate. https://scholargate.app/zh/bioinformatics/machine-learning-assisted-sequence-alignment
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