Network motifs and their origins      

Lewi Stone, Daniel Simberloff, Yael Artzy-Randrup, 2019.

Modern network science is a new and exciting research field that has transformed the study of complex systems over the last 2 decades. Of particular interest is the identification of small “network motifs” that might be embedded in a larger network and that indicate the presence of evolutionary design principles or have an overly influential role on system-wide dynamics. Motifs are patterns of interconnections, or subgraphs, that appear in an observed network significantly more often than in compatible randomized networks. The concept of network motifs was introduced into Systems Biology by Milo, Alon and colleagues in 2002, quickly revolutionized the field, and it has had a huge impact in wider scientific domains ever since. Here, we argue that the same concept and tools for the detection of motifs were well known in the ecological literature decades into the last century, a fact that is generally not recognized. We review the early history of network motifs, their evolution in the mathematics literature, and their recent rediscoveries.

Network motif examples. Motifs in different contexts (right column) and example systems (left column). (A) Checkerboard motif. For example, 4 species (A–D) occupy 5 islands (I₁–I₅). The checkerboard motif highlighted in red represents 2 species that do not co-occur on the same island (here, B appears on I₅ but D does not, and conversely, D appears on I₃ but B does not), suggestive of competitive interactions. (B) Triadic clustering motif. For example, the motif represents cases in which an individual’s connected friends are also connected with each other, having significance, for example, in social networks and epidemiological contact networks. (C) Feed-forward loop motif. For example, a circuit in gene transcription networks, in which DNA target β can be activated only through simultaneous binding of two transcription factors A and B, and in which B depends on A initially binding to DNA targets α and β, suggesting regulatory control on transcription.

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