Nature Communications (Oct 2021)
Objective comparison of methods to decode anomalous diffusion
- Gorka Muñoz-Gil,
- Giovanni Volpe,
- Miguel Angel Garcia-March,
- Erez Aghion,
- Aykut Argun,
- Chang Beom Hong,
- Tom Bland,
- Stefano Bo,
- J. Alberto Conejero,
- Nicolás Firbas,
- Òscar Garibo i Orts,
- Alessia Gentili,
- Zihan Huang,
- Jae-Hyung Jeon,
- Hélène Kabbech,
- Yeongjin Kim,
- Patrycja Kowalek,
- Diego Krapf,
- Hanna Loch-Olszewska,
- Michael A. Lomholt,
- Jean-Baptiste Masson,
- Philipp G. Meyer,
- Seongyu Park,
- Borja Requena,
- Ihor Smal,
- Taegeun Song,
- Janusz Szwabiński,
- Samudrajit Thapa,
- Hippolyte Verdier,
- Giorgio Volpe,
- Artur Widera,
- Maciej Lewenstein,
- Ralf Metzler,
- Carlo Manzo
Affiliations
- Gorka Muñoz-Gil
- ICFO – Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology
- Giovanni Volpe
- Department of Physics, University of Gothenburg
- Miguel Angel Garcia-March
- Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València
- Erez Aghion
- Max Planck Institute for the Physics of Complex Systems
- Aykut Argun
- Department of Physics, University of Gothenburg
- Chang Beom Hong
- Department of Physics, Pohang University of Science and Technology
- Tom Bland
- The Francis Crick Institute
- Stefano Bo
- Max Planck Institute for the Physics of Complex Systems
- J. Alberto Conejero
- Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València
- Nicolás Firbas
- Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València
- Òscar Garibo i Orts
- Instituto Universitario de Matemática Pura y Aplicada, Universitat Politècnica de València
- Alessia Gentili
- Department of Chemistry, University College London
- Zihan Huang
- School of Physics and Electronics, Hunan University
- Jae-Hyung Jeon
- Department of Physics, Pohang University of Science and Technology
- Hélène Kabbech
- Department of Cell Biology, Erasmus University Medical Center
- Yeongjin Kim
- Department of Physics, Pohang University of Science and Technology
- Patrycja Kowalek
- Faculty of Pure and Applied Mathematics, Hugo Steinhaus Center, Wrocław University of Science and Technology
- Diego Krapf
- Department of Electrical and Computer Engineering, Colorado State University
- Hanna Loch-Olszewska
- Faculty of Pure and Applied Mathematics, Hugo Steinhaus Center, Wrocław University of Science and Technology
- Michael A. Lomholt
- PhyLife, Department of Physics, Chemistry and Pharmacy, University of Southern Denmark
- Jean-Baptiste Masson
- Institut Pasteur, Université de Paris, USR 3756 (C3BI/DBC) & Neuroscience department CNRS UMR 3751, Decision and Bayesian Computation lab
- Philipp G. Meyer
- Max Planck Institute for the Physics of Complex Systems
- Seongyu Park
- Department of Physics, Pohang University of Science and Technology
- Borja Requena
- ICFO – Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology
- Ihor Smal
- Department of Cell Biology, Erasmus University Medical Center
- Taegeun Song
- Department of Physics, Pohang University of Science and Technology
- Janusz Szwabiński
- Faculty of Pure and Applied Mathematics, Hugo Steinhaus Center, Wrocław University of Science and Technology
- Samudrajit Thapa
- Institute of Physics & Astronomy, University of Potsdam
- Hippolyte Verdier
- Institut Pasteur, Université de Paris, USR 3756 (C3BI/DBC) & Neuroscience department CNRS UMR 3751, Decision and Bayesian Computation lab
- Giorgio Volpe
- Department of Chemistry, University College London
- Artur Widera
- Department of Physics and Research Center OPTIMAS, Technische Universität Kaiserslautern
- Maciej Lewenstein
- ICFO – Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology
- Ralf Metzler
- Institute of Physics & Astronomy, University of Potsdam
- Carlo Manzo
- ICFO – Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology
- DOI
- https://doi.org/10.1038/s41467-021-26320-w
- Journal volume & issue
-
Vol. 12,
no. 1
pp. 1 – 16
Abstract
Deviations from Brownian motion leading to anomalous diffusion are ubiquitously found in transport dynamics but often difficult to characterize. Here the authors compare approaches for single trajectory analysis through an open competition, showing that machine learning methods outperform classical approaches.
