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densityCut: an efficient and versatile topological approach for automatic clustering of biological data

Motivation: Many biological data processing problems can be formalized as clustering problems to partition data points into sensible and biologically interpretable groups. Results: This article introduces densityCut, a novel density-based clustering algorithm, which is both time- and space-efficient...

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Detalhes bibliográficos
Publicado no:Bioinformatics
Main Authors: Ding, Jiarui, Shah, Sohrab, Condon, Anne
Formato: Artigo
Idioma:Inglês
Publicado em: Oxford University Press 2016
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC5013902/
https://ncbi.nlm.nih.gov/pubmed/27153661
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btw227
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