Making Sense of Networks through Incoherence.

A new method for describing connections in real-world systems, including neural networks, genes, and social networks, has been developed by mathematicians at the University of Birmingham. The method involves mapping the hierarchies and incoherence within a system to predict its strong and weak points. The researchers found that it was possible to use trophic incoherence to estimate the point at which a network becomes strongly connected, which could be crucial in making decisions about infection control or treating epilepsy. The method works for any type of network, including those of neurons, people, species, metabolites, genes, and words, among others.