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Approximate Bayesian computation for estimating number concentrations of monodisperse nanoparticles in suspension by optical microscopy
RISE, SP – Sveriges Tekniska Forskningsinstitut.
2016 (English)In: Physical Review E. Statistical, Nonlinear, and Soft Matter Physics, ISSN 1539-3755, E-ISSN 1550-2376, Vol. 93, no 6, 063311Article in journal (Refereed) Published
Abstract [en]

We present an approximate Bayesian computation scheme for estimating number concentrations of monodisperse diffusing nanoparticles in suspension by optical particle tracking microscopy. The method is based on the probability distribution of the time spent by a particle inside a detection region. We validate the method on suspensions of well-controlled reference particles. We illustrate its usefulness with an application in gene therapy, applying the method to estimate number concentrations of plasmid DNA molecules and the average number of DNA molecules complexed with liposomal drug delivery particles. © 2016 American Physical Society.

Place, publisher, year, edition, pages
2016. Vol. 93, no 6, 063311
Keyword [en]
Bayesian networks, Gene therapy, Molecules, Nanoparticles, Probability distributions, Approximate Bayesian, Average numbers, DNA molecules, Mono-disperse, Monodisperse nanoparticles, Number concentration, Particle tracking, Reference particles, Suspensions (fluids)
National Category
Nano Technology
Identifiers
URN: urn:nbn:se:ri:diva-27644DOI: 10.1103/PhysRevE.93.063311OAI: oai:DiVA.org:ri-27644DiVA: diva2:1059516
Available from: 2016-12-22 Created: 2016-12-21 Last updated: 2017-01-29Bibliographically approved

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