Network Motifs and E. coli

Network motifs are small connected subnetworks within a larger network that occur in statistically significant quantities and may indicate functional regions of the network. Network motif software tools employ algorithms that compare a network to randomly generated networks in order to identify subnetworks that occur in frequencies higher than would be expected by random chance. The transcriptional regulation network of E. coli has been represented as a network and evaluated using both full enumeration and an edge sampling algorithm. Several significant network motifs were identified, including feedforward loops and bipartite graphs. This paper applies both full enumeration and a different sampling algorithm, randomized enumeration, to the E. coli network using the newer software tool FANMOD. Evaluating the E. coli transcriptional regulation network with FANMOD also identified feedforward loops and bipartite graphs as significant network motifs. Sampling identified fewer and less significant motifs than full enumeration, however, sampling enables the evaluation of larger subgraph sizes.