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Efficient implied alignment

BACKGROUND: Given a binary tree [Formula: see text] of n leaves, each leaf labeled by a string of length at most k, and a binary string alignment function ⊗, an implied alignment can be generated to describe the alignment of a dynamic homology for [Formula: see text] . This is done by first decorati...

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Detalles Bibliográficos
Autores principales: Washburn, Alex J., Wheeler, Ward C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7350648/
https://www.ncbi.nlm.nih.gov/pubmed/32646365
http://dx.doi.org/10.1186/s12859-020-03595-2
Descripción
Sumario:BACKGROUND: Given a binary tree [Formula: see text] of n leaves, each leaf labeled by a string of length at most k, and a binary string alignment function ⊗, an implied alignment can be generated to describe the alignment of a dynamic homology for [Formula: see text] . This is done by first decorating each node of [Formula: see text] with an alignment context using ⊗, in a post-order traversal, then, during a subsequent pre-order traversal, inferring on which edges insertion and deletion events occurred using those internal node decorations. RESULTS: Previous descriptions of the implied alignment algorithm suggest a technique of “back-propagation” with time complexity [Formula: see text] . Here we describe an implied alignment algorithm with complexity [Formula: see text] . For well-behaved data, such as molecular sequences, the runtime approaches the best-case complexity of Ω(k∗n). CONCLUSIONS: The reduction in the time complexity of the algorithm dramatically improves both its utility in generating multiple sequence alignments and its heuristic utility.