Complex networks serve as generic models for many biological systems that have
been shown to share a number of common structural properties such as power-law
degree distribution and small-worldness. Real-world networks are composed of
building blocks called motifs that are indeed specific subgraphs of (usually)
small number of nodes. Network motifs are important in the functionality of
complex networks, and the role of some motifs such as feed-forward loop in many
biological networks has been heavily studied. On the other hand, many biological
networks have shown some degrees of robustness in terms of their efficiency and
connectedness against failures in their components. In this paper we
investigated how random and systematic failures in the edges of biological
networks influenced their motif structure. We considered two biological
networks, namely, protein structure network and human brain functional network.
Furthermore, we considered random failures as well as systematic failures based
on different strategies for choosing candidate edges for removal. Failure in the
edges tipping to high degree nodes had the most destructive role in the motif
structure of the networks by decreasing their significance level, while removing
edges that were connected to nodes with high values of betweenness centrality
had the least effect on the significance profiles. In some cases, the latter
caused increase in the significance levels of the motifs.
Publisher: Public Library of Science
Date Published: 26-May-2011
Author(s): Mirzasoleiman B., Jalili M.