English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Stability landscapes are useful for understanding the properties of dynamicalsystems. These landscapes can be calculated from the system's dynamicalequations using the physical concept of scalar potential. Unfortunately, formost biological systems with two or more state variables such potentials do notexist. Here we use an analogy with art to provide an accessible explanation ofwhy this happens. Additionally, we introduce a numerical method for decomposingdifferential equations into two terms: the gradient term that has an associatedpotential, and the non-gradient term that lacks it. In regions of the statespace where the magnitude of the non-gradient term is small compared to thegradient part, we use the gradient term to approximate the potential asquasi-potential. The non-gradient to gradient ratio can be used to estimate thelocal error introduced by our approximation. Both the algorithm and aready-to-use implementation in the form of an R package are provided.

Climbing Escher's stairs: a way to approximate stability landscapes in multidimensional systems