Dataset Information

Objective comparison of methods to decode anomalous diffusion.

ABSTRACT: Deviations from Brownian motion leading to anomalous diffusion are found in transport dynamics from quantum physics to life sciences. The characterization of anomalous diffusion from the measurement of an individual trajectory is a challenging task, which traditionally relies on calculating the trajectory mean squared displacement. However, this approach breaks down for cases of practical interest, e.g., short or noisy trajectories, heterogeneous behaviour, or non-ergodic processes. Recently, several new approaches have been proposed, mostly building on the ongoing machine-learning revolution. To perform an objective comparison of methods, we gathered the community and organized an open competition, the Anomalous Diffusion challenge (AnDi). Participating teams applied their algorithms to a commonly-defined dataset including diverse conditions. Although no single method performed best across all scenarios, machine-learning-based approaches achieved superior performance for all tasks. The discussion of the challenge results provides practical advice for users and a benchmark for developers.

SUBMITTER: Munoz-Gil G

PROVIDER: S-EPMC8556353 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Objective comparison of methods to decode anomalous diffusion.

Muñoz-Gil Gorka G Volpe Giovanni G Garcia-March Miguel Angel MA Aghion Erez E Argun Aykut A Hong Chang Beom CB Bland Tom T Bo Stefano S Conejero J Alberto JA Firbas Nicolás N Garibo I Orts Òscar Ò Gentili Alessia A Huang Zihan Z Jeon Jae-Hyung JH Kabbech Hélène H Kim Yeongjin Y Kowalek Patrycja P Krapf Diego D Loch-Olszewska Hanna H Lomholt Michael A MA Masson Jean-Baptiste JB Meyer Philipp G PG Park Seongyu S Requena Borja B Smal Ihor I Song Taegeun T Szwabiński Janusz J Thapa Samudrajit S Verdier Hippolyte H Volpe Giorgio G Widera Artur A Lewenstein Maciej M Metzler Ralf R Manzo Carlo C

Nature communications 20211029 1

Deviations from Brownian motion leading to anomalous diffusion are found in transport dynamics from quantum physics to life sciences. The characterization of anomalous diffusion from the measurement of an individual trajectory is a challenging task, which traditionally relies on calculating the trajectory mean squared displacement. However, this approach breaks down for cases of practical interest, e.g., short or noisy trajectories, heterogeneous behaviour, or non-ergodic processes. Recently, se ...[more]

PMID: 34716305

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Dataset Information

Objective comparison of methods to decode anomalous diffusion.

Publications

Objective comparison of methods to decode anomalous diffusion.

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