K-medoids clustering.

Name: K-medoids clustering.
Published: 2015-09-28T03:10:10+00:00
License: https://creativecommons.org/licenses/by/4.0/
Keywords: residue Cys 436, egress channels, results show, 2 B 4 enzyme, type enzyme exhibits, structure characterization, root causes, side chain properties, bulk environment, Multiple Molecular Dynamics Simulations, mutation, thiolate group, md, F 429 Regulation, simulation, F 429H, Cpd 0, ferric hydroperoxo, phenylalanine 429 residue, Cluster analysis, site, species, Phe 429 residue, hydrogen bonds, cytochrome P 450, WT enzyme, dynamics ii, CYP 2 B 4

dataset

posted on 2015-09-28, 03:10 authored by Giordano Mancini, Costantino Zazza

For a given n_C (first row) the Dunn index (DI), the Davies-Bouldin index (DBI) and the size of the various clusters are shown. The column showing the best n_C value is typed in italics. Frame set #1 was used in the analysis.

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K-medoids clustering.

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