Single-molecule localization microscopy (SMLM) generates data in the form of coordinates of localized fluorophores. Cluster analysis is an attractive route for extracting biologically meaningful ...

Adult-onset diabetes mellitus (here: aDM) is not a uniform disease entity. In European populations, five diabetes subgroups have been identified by cluster analysis using simple clinical variables; ...

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on technique for visualizing and clustering data. A self-organizing map (SOM) is a data structure that can be used ...

Conventional clustering techniques often focus on basic features like crystal structure and elemental composition, neglecting target properties such as band gaps and dielectric constants. A new study ...

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Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...

Spectral clustering is quite complex, but it can reveal patterns in data that aren't revealed by other clustering techniques. Data clustering is the process of grouping data items so that similar ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

Microsoft Excel’s Data Analysis Toolpak is an invaluable add-in for those who require complex statistical or engineering analyses. This powerful feature allows users to execute a variety of data ...