Focused multidimensional scaling: interactive visualization for exploration of high-dimensional data

Abstract Background Visualization is an important tool for generating meaning from scientific data, but the visualization of structures in high-dimensional data (such as from high-throughput assays) presents unique challenges. Dimension reduction methods are key in solving this challenge, but these...

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Bibliografische Detailangaben

Hauptverfasser:	Lea M. Urpa, Simon Anders
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	BMC 2019-05-01
Schriftenreihe:	BMC Bioinformatics
Schlagworte:	Clustering High-dimensional data Visualization Personalized medicine
Online-Zugang:	http://link.springer.com/article/10.1186/s12859-019-2780-y
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