The results of the AnDi challenge 2020 are now published in the article: Muñoz-Gil et al. Objective comparison of methods to decode anomalous diffusion, Nature Communications 12:6253 (2021).
Stay tuned! We are currently organizing the 2nd edition of the AnDi challenge (Results of the first edition can be found here.)
Since Albert Einstein provided a theoretical foundation for Robert Brown’s observation of the movement of particles within pollen grains suspended in water, significant deviations from the laws of Brownian motion have been uncovered in a variety of animate and inanimate systems, from biology to the stock market. Anomalous diffusion, as it has come to be called, is a widespread phenomenon connected to non-equilibrium phenomena, flows of energy and information, and transport in living systems. Just focusing on life sciences, identifying its underlying mechanism is a crucial step to understanding, e.g., the motion of sub-cellular components, the uptake of drugs, nonrandom distributions and lateral segregation of plasma membrane components, and the role of chromatin diffusion in gene regulation.
However, the measurement of these properties from the data analysis of trajectories is often limited, especially for trajectories that are short, irregularly sampled, or featuring mixed behaviors. In the last years, several methods have been proposed to quantify anomalous diffusion, going beyond the classical calculation of the mean squared displacement. The ultimate goal is to provide a computational tool to be used conventionally in experiments from a large variety of fields (we have already applied it to ultracold atoms, membrane cells, etc) for which the short, irregularly sampled, mixed trajectories measured hinder to characterize the kind of diffusion with the traditional averaged strategies.