Exploring noise, degeneracy, and determinism in biological networks with the einet package
- Understanding noise in networks and finding the right scale to represent a system are important problems in network biology. Most research focuses on the raw, micro-scale network from data/simulations and seldom explores the scale-dependence of properties.
- Here, we introduce the einet package, which looks at the most informative scale in a biological network using recent concepts from information theory and network science.
- einet uses two metrics: Effective information, which measures the interplay between degeneracy and determinism in a network’s edges, and causal emergence, which finds the scale of the network with the highest effective information.
- einet is available in R and Python and provides tools to explore noise and scale dependency in networks as well as compare information flow and noise across networks.