Fig. 1

HiLoop terminology and workflow. a Examples of simple positive feedback loops vs. high-feedback loops. Each colored cycle is a different positive feedback loop. In high-feedback loops, one regulation may be part of multiple simple feedback loops, in which case it can be visualized as a multiedge. b Summary of HiLoop features and workflow. To search for high-feedback motifs, a network must be specified. This may be either a user-defined network or a subgraph of a larger existing network. Instances of various high-feedback topologies can be extracted from the input network. The upper left box shows the full list of supported cycle interconnection patterns. Cycles may contain regulations of different signs (round-head arrows) as long as the net sign matches the motif definition (+/− signs). Interconnected cycles providing high feedback are highlighted (1). To detect enrichment, the frequency of loops or specified high-feedback topologies in the input network can be compared with the frequency in randomly permuted networks (2). Detected high-feedback topologies can be modeled with sampled parameter sets and many initial conditions to visualize attractors of the different systems the network may give rise to (3). Lower-left graph depicts the TRRUST2 network with activations in blue and repressions in red; upper-middle graph depicts a subgraph of the T cell network where nodes A through F represent Eprotein, HEBAlt, Gfi1, E2A, Ikaros, and PU1 respectively