The dark side of network analysis: Poorly defined and fragile network metrics
Channel: Lars Juhl Jensen
Date: 2021-10-25

A look at the dark side of the metrics commonly used for analysis of biological networks. The presentation first recaps the issues related to interpretations, which I already brought up in an earlier presentation, before explaining the problems of defining certain metrics for networks with disconnected components, how path-based metrics are fragile, and why these problems badly affect network analysis of biological networks. Finally, I briefly explain why I think the best, and possibly only, solution is to simply stop using these metrics for biological network analysis. You may want to watch my short introduction to the core concepts of network analysis first: https://youtu.be/GbqoSXVqrxE

0:00 Introduction: major problems that are rarely talked about, network characterization, and network analysis
0:26 Recap: scale-free topology and science funding, degree centrality and study bias, and path analysis in networks with no flow
1:05 Poorly defined metrics: characteristic path length, network diameter, disconnected components, infinite distances, and component vs. network metrics
2:39 Path fragility: shortest paths, the effect of removing or adding one edge, and impact on betweenness centrality and global metrics
3:39 Main application area: large biological networks, false positives / negatives are unavoidable, disconnected components are the rule, and this breaks all path metrics
4:24 What should we do: do nothing, fragile metrics will fail, it cannot be fixed, so just avoid them