Testing our algorithm on signaling network SN5 and SN6. Because of

Testing our algorithm on signaling network SN5 and SN6. Because of the high growth of the number of subgraphs, these large networks were tested for subgraphs of size 3, 4, and 5. The VF2 algorithm is not tested because it requires a large amount of times to detect subgraphs on the signaling network SN5 and SN6 and it shows memory overflow on signaling network with more than 8000 nodes for detecting 3-node subgraphs (data not shown). Since the speed of our algorithm was obtained from real signaling networks, we consider the run-time of detecting regulatory motifs against the any sizes of signaling networks can be estimated by interpolating or extrapolating our experimental results.ResultsTo illustrate the effectiveness of RMOD in signaling network, we explain the functionalities of interactive analysis and the auxiliary tools that make it possible to identify regulatory motifs and analyze their structural properties. Then we show each step of the regulatory motif analysis, staring from the network creation and ending with the visualization of the analyzed network with an example of apoptosis regulation network [28]. This example is also available for review on the RMOD web page: http://pks.kaist.ac. kr/rmod.such as activation and inhibition. RMOD allows users to create regulatory networks either by uploading the input data file or by selecting and editing preloaded network files in the network editor interface. It accepts the input data files in a format where the first, second, third columns denote regulator, relation, and target, respectively. The regulator and the target can 23148522 be any string label, but the relation contains only of two predefined characters, such as + and 2, which correspond to activation and inhibition, respectively. Users can also modify and update any selected network via network viewer or data tables by adding or Title Loaded From File deleting the nodes and edges in the network. In Figure 7, we show the network editor interface 18055761 with an example of uploaded apoptosis regulation network with 11 nodes and 15 edges. As shown in Figure 7, the network elements in apoptosis regulation network show various color and shape in the network editor interface. This is because the RMOD represents the structural properties with different color and shape. The nodes with only inward edges are marked as input nodes, and the ones with only outward edges are marked as output nodes. The edges also have different color and shape depending on their properties, such as activation and inhibition.Generating Query Regulatory MotifsIn order to identify regulatory motifs against the input network, it is necessary to define query regulatory motifs, which are compressed forms of regulatory networks representing specific regulatory properties. Currently, since small numbers of regulatory motifs were identified by using mathematical modeling and simulation, RMOD provides flexible methods for generatingCreating a NetworkThe first step in analyzing regulatory motif is to create a regulatory network where the edge represents the regulatory effect,RMOD: Regulatory Motif Detection ToolFigure 8. The motif order Tubastatin-A designer interface. The motif designer enables users to select or create query regulatory motifs. doi:10.1371/journal.pone.0068407.gquery regulatory motifs via the motif designer interface. RMOD allows users to select known regulatory motifs or edit the nodes and edges to build novel regulatory motifs in the motif designer interface. As described in Materials and methods secti.Testing our algorithm on signaling network SN5 and SN6. Because of the high growth of the number of subgraphs, these large networks were tested for subgraphs of size 3, 4, and 5. The VF2 algorithm is not tested because it requires a large amount of times to detect subgraphs on the signaling network SN5 and SN6 and it shows memory overflow on signaling network with more than 8000 nodes for detecting 3-node subgraphs (data not shown). Since the speed of our algorithm was obtained from real signaling networks, we consider the run-time of detecting regulatory motifs against the any sizes of signaling networks can be estimated by interpolating or extrapolating our experimental results.ResultsTo illustrate the effectiveness of RMOD in signaling network, we explain the functionalities of interactive analysis and the auxiliary tools that make it possible to identify regulatory motifs and analyze their structural properties. Then we show each step of the regulatory motif analysis, staring from the network creation and ending with the visualization of the analyzed network with an example of apoptosis regulation network [28]. This example is also available for review on the RMOD web page: http://pks.kaist.ac. kr/rmod.such as activation and inhibition. RMOD allows users to create regulatory networks either by uploading the input data file or by selecting and editing preloaded network files in the network editor interface. It accepts the input data files in a format where the first, second, third columns denote regulator, relation, and target, respectively. The regulator and the target can 23148522 be any string label, but the relation contains only of two predefined characters, such as + and 2, which correspond to activation and inhibition, respectively. Users can also modify and update any selected network via network viewer or data tables by adding or deleting the nodes and edges in the network. In Figure 7, we show the network editor interface 18055761 with an example of uploaded apoptosis regulation network with 11 nodes and 15 edges. As shown in Figure 7, the network elements in apoptosis regulation network show various color and shape in the network editor interface. This is because the RMOD represents the structural properties with different color and shape. The nodes with only inward edges are marked as input nodes, and the ones with only outward edges are marked as output nodes. The edges also have different color and shape depending on their properties, such as activation and inhibition.Generating Query Regulatory MotifsIn order to identify regulatory motifs against the input network, it is necessary to define query regulatory motifs, which are compressed forms of regulatory networks representing specific regulatory properties. Currently, since small numbers of regulatory motifs were identified by using mathematical modeling and simulation, RMOD provides flexible methods for generatingCreating a NetworkThe first step in analyzing regulatory motif is to create a regulatory network where the edge represents the regulatory effect,RMOD: Regulatory Motif Detection ToolFigure 8. The motif designer interface. The motif designer enables users to select or create query regulatory motifs. doi:10.1371/journal.pone.0068407.gquery regulatory motifs via the motif designer interface. RMOD allows users to select known regulatory motifs or edit the nodes and edges to build novel regulatory motifs in the motif designer interface. As described in Materials and methods secti.