Real-time single-molecule 3D tracking in E. coli based on cross-entropy minimization
https://doi.org/10.17044/SCILIFELAB.21602844
General description
This item contains all the data, code and analysis objects used in the paper:
"Real-time single-molecule 3D tracking in E. coli based on cross-entropy minimization"
Elias Amselem*, Bo Broadwater*, Tora Hävermark, Magnus Johansson & Johan Elf.
Dept. Cell and Molecular Biology, Uppsala University, Sweden"
*Equal contribution
We present a 3D tracking principle that approaches the sub-ms regime. The method is based on the true excitation point spread function and cross-entropy minimization for position localization of moving fluorescent reporters. Our implementation also features a new method for microsecond 3D point spread function positioning and a new estimator for diffusion analysis of tracking data. We successfully applied these methods to track the Trigger Factor protein in living bacterial cells.
Experimental data description
The data provided in this repository is generated by the microscope described in the publication mentioned above. The underlying real-time tracking principle and methods used are outlined and evaluated using the code base and data found in this repository. This includes; the trajectory reconstruction based on the cross-entropy minimization, the extended covariance estimator (ECVE) for diffusion, simulation for evaluating both trajectory reconstruction and ECVE method, and the Trigger Factor live cell E. coli data with analysis.
Each entry includes the raw data with analysis code. In each entry under the folder "TriggerFactor_Code\ProjectMain"
is the main analysis python file, this file includes instructions on how to run the script. Also, in the folder there are preconfigured main files to generate data used in the manuscript, this is also available in the ScourceData.zipÖppnas i en ny tabb file.
To understand how to use the code and the structure used please see entry:
20220722_EXP-22-BL9428_Example_Analysis
and the README.txt file included. Here you find the python requirements (dependencies and versions), and instructions on how to run simulations.
Gå till källa för data
Öppnas i en ny tabbhttps://doi.org/10.17044/SCILIFELAB.21602844
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Uppsala universitet