A novel method for automatic single molecule tracking of blinking molecules at low intensities
文献情報
Christoph Kölbl, Beate Stempfle
Single molecule tracking provides unprecedented insights into diffusional processes of systems in life and material sciences. Determination of molecule positions with high accuracy and correct connection of the determined positions to tracks is a challenging task with, so far, no universal solution for single fluorescing molecules tackling the challenge of low signal-to-noise ratios, frequent blinking and photo bleaching. Thus, the development of novel algorithms for automatic single molecule fluorescence tracking is essential to analyse the huge amount of diffusional data obtained with single molecule widefield fluorescence microscopy. Here, we present a novel tracking model using a top-down polyhedral approach which can be implemented effectively using standard linear programming solvers. The results of our tracking approach are compared to the ground truth of simulated data with different diffusion coefficients, signal-to-noise ratios and particle densities. We also determine the dependency of blinking on the analysed distribution of diffusion coefficients. To confirm the functionality of our tracking method, the results of automatic tracking and manual tracking by a human expert are compared and discussed.
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.











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