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Variational Algorithms for Analyzing Noisy Multistate Diffusion Trajectories
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.ORCID iD: 0000-0003-4200-0191
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
2018 (English)In: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 115, no 2, p. 276-282Article in journal (Refereed) Published
Abstract [en]

Single-particle tracking offers a noninvasive high-resolution probe of biomolecular reactions inside living cells. However, efficient data analysis methods that correctly account for various noise sources are needed to realize the full quantitative potential of the method. We report algorithms for hidden Markov-based analysis of single-particle tracking data, which incorporate most sources of experimental noise, including heterogeneous localization errors and missing positions. Compared to previous implementations, the algorithms offer significant speedups, support for a wider range of inference methods, and a simple user interface. This will enable more advanced and exploratory quantitative analysis of single-particle tracking data.

Place, publisher, year, edition, pages
CELL PRESS , 2018. Vol. 115, no 2, p. 276-282
National Category
Biophysics
Identifiers
URN: urn:nbn:se:uu:diva-361691DOI: 10.1016/j.bpj.2018.05.027ISI: 000438958800014PubMedID: 29937205OAI: oai:DiVA.org:uu-361691DiVA, id: diva2:1253059
Conference
Biophysical-Society Thematic Meeting on Single-Cell Biophysics - Mearurement, Modulation, and Modeling, JUN, 2017, Natl Taiwan Univ, Acad Sinica, Inst Atom & Mol Sci, Taipei, TAIWAN
Funder
Knut and Alice Wallenberg FoundationEU, European Research Council, ERC-2013-CoG 616047 SMILEAvailable from: 2018-10-03 Created: 2018-10-03 Last updated: 2018-10-03Bibliographically approved

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Lindén, MartinElf, Johan

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