10.1371/journal.pone.0169661.g002
Alexander Karsakov
Alexander
Karsakov
Thomas Bartlett
Thomas
Bartlett
Artem Ryblov
Artem
Ryblov
Iosif Meyerov
Iosif
Meyerov
Mikhail Ivanchenko
Mikhail
Ivanchenko
Alexey Zaikin
Alexey
Zaikin
Determining the edge weight between ZFP106 and TRIM9 genes.
Public Library of Science
2017
classification
15295 gene methylation levels
Parenclitic Network Analysis
control group subjects
DNA methylation data
12 network topology indices
power-law node degree distribution
parenclictic networks
2017-01-20 17:33:03
Figure
https://plos.figshare.com/articles/figure/Determining_the_edge_weight_between_ZFP106_and_TRIM9_genes_/4574272
<p>Each point corresponds to gene methylation levels in the control group (green), other BRCA-negative (blue) and BRCA-positive (red) subjects. The solid line shows the linear regression <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0169661#pone.0169661.e001" target="_blank">model (1)</a>. While the data sets for healthy and tumour samples are quite distinct, the mismatch <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0169661#pone.0169661.e002" target="_blank">Eq (2)</a> is of the same order of magnitude for both classes. Employing the Mahalanobis distance <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0169661#pone.0169661.e003" target="_blank">Eq (3)</a> overcomes this problem.</p>