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An algorithm-centric Monte Carlo method to empirically quantify motion type estimation uncertainty in single-particle tracking
Alessandro Rigano, Vanni Galli, Krzysztof Gonciarz, Ivo F. Sbalzarini, View ORCID ProfileStrambio-De-Castillia Caterina
doi: https://doi.org/10.1101/379255
Alessandro Rigano
1Program In Molecular Medicine University of Massachusetts Medical School Worcester, MA 01605
Vanni Galli
2Istituto Sistemi Informativi e Networking, Scuola Universitaria Professionale della Svizzera Italiana, CH-6928 Manno, Switzerland
Krzysztof Gonciarz
3MOSAIC Group, Center for Systems Biology Dresden; TU Dresden, Faculty of Computer Science; Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr. 108, 01307 Dresden, Germany
Ivo F. Sbalzarini
3MOSAIC Group, Center for Systems Biology Dresden; TU Dresden, Faculty of Computer Science; Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstr. 108, 01307 Dresden, Germany
Strambio-De-Castillia Caterina
1Program In Molecular Medicine University of Massachusetts Medical School Worcester, MA 01605
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Posted August 08, 2018.
An algorithm-centric Monte Carlo method to empirically quantify motion type estimation uncertainty in single-particle tracking
Alessandro Rigano, Vanni Galli, Krzysztof Gonciarz, Ivo F. Sbalzarini, Strambio-De-Castillia Caterina
bioRxiv 379255; doi: https://doi.org/10.1101/379255
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