The article by Shen-Orr et al. (2002) explores the design principles of transcriptional regulation networks in *Escherichia coli* by identifying and analyzing network motifs. Network motifs are recurring patterns of interconnections that occur more frequently in the network than in randomized networks. The authors define three significant motifs: feedforward loops, single-input modules (SIMs), and dense overlapping regulons (DORs). Feedforward loops involve a general transcription factor regulating a specific factor, which together regulates multiple operons. SIMs consist of operons controlled by a single transcription factor, often autoregulatory. DORs are dense regions of overlapping interactions between operons and a group of input transcription factors. These motifs are found to be highly significant in the *E. coli* network, with most feedforward loops being coherent (co-regulating with the same sign). The motifs help in understanding the network's function, such as generating temporal expression programs and responding to external signals. The study also suggests that these motifs may serve as basic computational elements in other biological networks.The article by Shen-Orr et al. (2002) explores the design principles of transcriptional regulation networks in *Escherichia coli* by identifying and analyzing network motifs. Network motifs are recurring patterns of interconnections that occur more frequently in the network than in randomized networks. The authors define three significant motifs: feedforward loops, single-input modules (SIMs), and dense overlapping regulons (DORs). Feedforward loops involve a general transcription factor regulating a specific factor, which together regulates multiple operons. SIMs consist of operons controlled by a single transcription factor, often autoregulatory. DORs are dense regions of overlapping interactions between operons and a group of input transcription factors. These motifs are found to be highly significant in the *E. coli* network, with most feedforward loops being coherent (co-regulating with the same sign). The motifs help in understanding the network's function, such as generating temporal expression programs and responding to external signals. The study also suggests that these motifs may serve as basic computational elements in other biological networks.