The study of motifs plays a central role in recognition of relations among components in biological networks such that gene regulation, protein interaction, and metabolic networks. Since these relations are not well-known, motifs inference appears as a way for understanding the principles involved in the relationship between cellular components. On the other hand, motifs search is a basic step for constructing models which represent biological behavior and explain functional and/or structural effects in biological networks. In this work we address the problem of infer all relevant motifs in a biological network. We also provide a solution for searching colorful motifs which can be topological-free or have an acyclic topology. We developed a tool for searching and inferring motifs, named SIMBio, and we implemented sequential and parallel versions. When comparing performance, our experiments have showed that SIMBio is faster than MOTUS for inferring motifs, even in the sequential version. We also compared it to Torque, and SIMBio has found more occurrences of motifs under the same experiments.
['Diego P. Rubert', 'Eloi Araujo', 'Marco A. Stefanes']
SIMBio: Searching and inferring colorful motifs in biological networks