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Extracting intracellular diffusive states and transition rates from single-molecule tracking data
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
2013 (English)In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 10, no 3, 265-269 p.Article in journal (Refereed) Published
Abstract [en]

We provide an analytical tool based on a variational Bayesian treatment of hidden Markov models to combine the information from thousands of short single-molecule trajectories of intracellularly diffusing proteins. The method identifies the number of diffusive states and the state transition rates. Using this method we have created an objective interaction map for Hfq, a protein that mediates interactions between small regulatory RNAs and their mRNA targets.

Place, publisher, year, edition, pages
2013. Vol. 10, no 3, 265-269 p.
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Natural Sciences
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URN: urn:nbn:se:uu:diva-199738DOI: 10.1038/NMETH.2367ISI: 000316650800026OAI: oai:DiVA.org:uu-199738DiVA: diva2:621007
Available from: 2013-05-13 Created: 2013-05-13 Last updated: 2017-12-06Bibliographically approved

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Persson, FredrikLinden, MartinUnoson, CeciliaElf, Johan

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