Numeric Lyndon-based feature embedding of sequencing reads for machine learning approaches

DOI10.1016/j.ins.2022.06.005arXiv2202.13884OpenAlexW4281758821MaRDI QIDQ6195191

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Publication date: 13 March 2024

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2202.13884

zbMATH Keywords

machine learningLyndon factorizationread representationbiological sequence embedding

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Protein sequences, DNA sequences (92D20)

Cites Work

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• The origins of combinatorics on words
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• On the longest common prefix of suffixes in an inverse Lyndon factorization and other properties
• Factorizing words over an ordered alphabet
• A new characterization of maximal repetitions by Lyndon trees
• On Burnside's Problem
• Free differential calculus. IV: The quotient groups of the lower central series
• SPADE: An efficient algorithm for mining frequent sequences

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