Comparing Three Notions of Discrete Ricci Curvature on Biological Networks

TL;DR

This paper compares three discrete Ricci curvature notions on biological networks to understand their robustness, introduces a signed-control Ricci curvature for directed networks, and relates these to traditional network measures.

Contribution

It introduces a signed-control Ricci curvature for directed biological networks and compares three existing Ricci curvature notions on biological data.

Findings

Similar results from different Ricci curvature notions on biological networks

Signed-control Ricci curvature captures directionality and sign information in networks

Curvature measures relate to betweenness centrality and clustering coefficients

Abstract

In the present work, we study the properties of biological networks by applying analogous notions of fundamental concepts in Riemannian geometry and optimal mass transport to discrete networks described by weighted graphs. Specifically, we employ possible generalizations of the notion of Ricci curvature on Riemannian manifold to discrete spaces in order to infer certain robustness properties of the networks of interest. We compare three possible discrete notions of Ricci curvature (Olivier Ricci curvature, Bakry-\'Emery Ricci curvature, and Forman Ricci curvature) on some model and biological networks. While the exact relationship of each of the three definitions of curvature to one another is still not known, they do yield similar results on our biological networks of interest. These notions are initially defined on positively weighted graphs; however, Forman-Ricci curvature can also be defined on directed positively weighted networks. We will generalize this notion of directed Forman Ricci curvature on the network to a form that also considers the signs of the directions (e. g., activator and repressor in transcription networks). We call this notion the \emph{signed-control Ricci curvature}. Given real biological networks are almost always directed and possess positive and negative controls, the notion of signed-control curvature can elucidate the network-based study of these complex networks. Finally, we compare the results of these notions of Ricci curvature on networks to some known network measures, namely, betweenness centrality and clustering coefficients on graphs.