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机器学习辅助序列比对×系统发育分析×
领域生物信息学生物信息学
方法族Process / pipelineProcess / pipeline
起源年份2010s–2020s (deep learning era, accelerating post-2017)1960s-1981 (distance trees ~1967; ML framework formalised 1981)
提出者Multiple contributors; notable milestones include Llinares-López et al. (DEDAL, 2023) and Jumper et al. (AlphaFold MSA module, 2021)Joseph Felsenstein (maximum likelihood framework); Walter Fitch and Emanuel Margoliash (distance methods)
类型Computational pipeline / supervised and self-supervised learningComputational inference method
开创性文献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 ↗Felsenstein, J. (2004). Inferring Phylogenies. Sinauer Associates. ISBN: 978-0878931774
别名ML-guided alignment, deep learning sequence alignment, neural sequence alignment, AI-assisted MSAmolecular phylogenetics, phylogenetic inference, evolutionary tree reconstruction, phylogenomics
相关15
摘要Machine learning-assisted sequence alignment uses statistical learning models — including deep neural networks and protein language models — to compute biologically meaningful alignments between nucleotide or amino acid sequences. By learning substitution patterns and structural constraints from large training corpora, these methods surpass classical scoring matrices (e.g., BLOSUM, PAM) in sensitivity for remote homologs and structurally constrained regions, making them the current state of the art for difficult alignment tasks in genomics and proteomics.Phylogenetic analysis reconstructs the evolutionary history of organisms, genes, or proteins by comparing molecular sequence data and estimating the branching tree that best explains observed similarities and differences. Rooted in the work of Felsenstein and colleagues from the 1960s onward, it is a cornerstone technique in evolutionary biology, microbiology, epidemiology, and comparative genomics, supporting tasks from tracing viral outbreak origins to classifying novel species.
ScholarGate数据集
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  2. 2 来源
  3. PUBLISHED

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ScholarGate方法对比: Machine learning-assisted sequence alignment · Phylogenetic Analysis. 于 2026-06-15 检索自 https://scholargate.app/zh/compare