Explore network modules for Campylobacter jejuni

Use residual and motif e-value sliders to filter modules

Residual: 0-0.3 Motif e-value 0-10
This is the section to display the module list


Cj0061c fliA Cj0101 Cj0123c Cj0135 Cj0287c greA Cj0322 perR Cj0368c Cj0382c nusB Cj0394c Cj0400 fur Cj0440c Cj0460 nusA Cj0466 Cj0473 nusG Cj0479 rpoC Cj0480c Cj0518 htpG Cj0571 Cj0670 rpoN Cj0757 hrcA Cj0883c Cj1000 Cj1001 rpoD Cj1024c Cj1042c Cj1050c Cj1103 csrA Cj1156 rho Cj1230 hspR Cj1253 pnp Cj1273c rpoZ Cj1349c Cj1533c Cj1546 Cj1552c Cj1556 Cj1561 Cj1563c Cj1595 rpoA
Network Exploration Help

This page gives you overview of the network modules for a particular organism. You can explore these modules by using various filters.

Currently we support two filters, Residual and Motif e-values. Network modules are loaded with default residual and motif e-value filters. In order to change filters, simply move the slider to select the desired range. Results table will automatically update to reflect your filter selections. If you would like to remove filters, click on "Reset Filters" button.

Network Table

Network table will show the following columns for each module.

Module: Number of the module for the given version of the network.

Residual: is a measure of bicluster quality. Mean bicluster residual is smaller when the expression profile of the genes in the module is "tighter". So smaller residuals are usually indicative of better bicluster quality.

Expression Profile: is a preview of the expression profiles of all the genes under subset of conditions included in the module. Tighter expression profiles are usually indicative of better bicluster quality.

Motif e-value: cMonkey tries to identify two motifs per modules in the upstream sequences of the module member genes. Motif e-value is an indicative of the motif co-occurences between the members of the module.Smaller e-values are indicative of significant sequence motifs. Our experience showed that e-values smaller than 10 are generally indicative of significant motifs.

Genes: Number of genes included in the module.

Functions: We identify functional enrichment of each module by camparing to different functional categories such as KEGG, COG, GO etc. by using hypergeometric function. If the module is significantly enriched for any of the functions, this column will list few of the these functions as an overview. Full list of functions is available upon visiting the module page under the Functions tab.


Inferelator algorithm identifies most probable regulatory influences for each module. These influences can be transcription factors or environmental factors. Influences section lists all the regulators that have influences on modules. Click on the regulator name If you would like to access which modules are regulated by these regulators.