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Updated: Apr 25, 2026

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
Published on: February 9, 2017
Modeling temporal networks using random itineraries
Alain Barrat1, Bastien Fernandez2, Kevin K Lin3
1Centre de Physique Théorique, Aix-Marseille Université, CNRS UMR 7332, Université de Toulon, 13288 Marseille cedex 9, France and Data Science Lab, Institute for Scientific Interchange (ISI) Foundation, Torino 10126, Italy.
Abstract:
We propose a procedure to generate dynamical networks with bursty, possibly repetitive and correlated temporal behaviors. Regarding any weighted directed graph as being composed of the accumulation of paths between its nodes, our construction uses random walks of variable length to produce time-extended structures with adjustable features. The procedure is first described in a general framework. It is then illustrated in a case study inspired by a transportation system for which the resulting synthetic network is shown to accurately mimic the empirical phenomenology.
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