On motifs in colored graphs

TL;DR

This paper investigates the detection of network motifs in vertex-colored graphs, providing complexity results, efficient algorithms for specific cases, and a probabilistic approach, with experiments demonstrating practical effectiveness.

Contribution

It introduces new algorithms and complexity analyses for motif detection in colored graphs, along with a probabilistic method for identifying frequent motifs.

Findings

Algorithms are efficient and competitive on real data

Complexity results for motif detection problems

Probabilistic strategy effectively finds frequent motifs

Abstract

One of the most important concepts in biological network analysis is that of network motifs, which are patterns of interconnections that occur in a given network at a frequency higher than expected in a random network. In this work we are interested in searching and inferring network motifs in a class of biological networks that can be represented by vertex-colored graphs. We show the computational complexity for many problems related to colorful topological motifs and present efficient algorithms for special cases. We also present a probabilistic strategy to detect highly frequent motifs in vertex-colored graphs. Experiments on real data sets show that our algorithms are very competitive both in efficiency and in quality of the solutions.