Figure 1.
Known regulatory motifs in non-isomorphic relationship.
(a) Oscillation motif (b) Adaptation motif (c) Bistable switch motif. A, B, C in the circle represent enzymes that catalyze reaction in their active state, For example, A → B indicates that A converts B from its inactive state to active state and A ⊣ B indicates that A convert B from its active state to inactive state. * means that the network size should be more than equal to three for exhibiting dynamic behaviour.
Figure 2.
Overview of regulatory motif identification process.
Figure 3.
The construction of a path-tree for the adaptation motif as an example.
Figure 4.
The process of searching for adaptation motif in the input network as an example.
Table 1.
Signaling networks generated from the integration of signaling pathways.
Figure 5.
The Web server hosts the RMOD Web application and accepts user requests via standard Web browsers. The RMOD server handles user requests for network and query management, run the network analysis pipeline and presents the result of analyzed input via network viewer. The file management module stores all network, regulatory motif and job-related data.
Figure 6.
The run-time comparisons between the RMOD and the VF2 algorithm.
The average run-times of searching for all occurrences of a subgraph were measured against various signaling networks. Illustrated results are for (a) 3-node subgraph search (b) 4-node subgraph search (c) 5-node subgraph search (d) 6-node subgraph search. Times are given in milliseconds (ms).
Table 2.
Computational cost for RMOD algorithm on large signaling networks.
Figure 7.
The network editor allows users to create or edit input network.
Figure 8.
The motif designer enables users to select or create query regulatory motifs.
Figure 9.
The motif explorer allows users to analyze the input network and show the result of regulatory motif analysis.