This page provides data and source codes associated with the following paper:
 K. Agarwal and R. Machan, Multiple Signal Classification Algorithm for super-resolution fluorescence microscopy, Nature Communications, vol. 7, article id. 13752, 2016. (impact factor = 12.124) (Preprint and an easily readable supplement PDF) (PDF)
 K. Agarwal and D.K. Prasad, "Eigen-analysis reveals components supporting super-resolution imaging of blinking fluorophores", Scientific Reports, vol. 7, 2017. (impact factor = 4.259) (Source code)(PDF)
 K. Agarwal, R. Machan, and D. K. Prasad, “Non-heuristic automatic techniques for overcoming low signal-to-noise-ratio bias of localization microscopy and multiple signal classification algorithm”, Scientific Reports, 2018. (impact factor = 4.259)(source code and PDF)
Single molecule localization techniques are restricted by long acquisition and computational times, or the need of special fluorophores or biologically toxic photochemical environments. We propose a statistical super-resolution technique of wide-field fluorescence microscopy called MUltiple SIgnal Classification ALgorithm (MUSICAL) which has several advantages. It provides resolution down to at least 50 nm, requires less frames and lower excitation power, and works even at high fluorophore concentrations. Further, it works with any fluorophore that exhibits blinking on the time scale of the recording. Multiple signal classification algorithm shows comparable or better performance in comparison with single molecule localization techniques and four contemporary statistical super-resolution methods for experiments of in-vitro actin filaments and other independently acquired experimental datasets. We also demonstrate super-resolution at time scales of 245 ms (using 49 frames acquired at 200 frames per second) in samples of live-cell microtubules and live-cell actin filaments imaged without imaging buffers.
The video: https://www.youtube.com/watch?v=deCu_tXoIoY
The code usage: https://www.youtube.com/watch?v=k3A5al8AGG4
The ImageJ Plugin video - How to use JMUSICAL - https://www.youtube.com/watch?v=CsJHqSQb11E
Dataset generated for this paper:
In-vitro samples 1- 3:
These are samples of actin filaments tagged with Phalloidin-Atto 565. The emission wavelength is 593 nm. Sample details are available in methods and Supplementary Table 2. Details are also given in the read me file with each sample.
Live cell microtubule samples 1-2:
These are sample of CHO-K1 cells in which tubulin is tagged with Lifeact-GFP. Sample details are available in methods and Supplementary Table 2. Details are also given in the read me file with each sample.
Live cell F-actin sample:
This is a sample of CHO-K1 cells in which F-actin is tagged with Lifeact-GFP. Sample details are available in methods and Supplementary Table 2. Details are also given in the read me file with each sample.
Live cell F-actin sample (data download link)(file size-116 MB)
Data of synthetic examples used in supplementary information is given below. Details about the examples appear in Supplementary Methods 2. Details, where possible, have been included in the read me file with each example.
SynEx1 (data download link)(file size-10 kb)
SynEx2 (data download link)(file size-194 kb)
SynEx3 (data download link)(file size-11.7 MB)
SynEx4 (data download link)(file size-1.49 MB)
SynPairDelX (data download link)(file size-20.8 MB)
SynPeriod (data download link)(file size-980 kb)
SynFork (data download link)(file size-6.52 MB)
SynSTORM (data download link)(file size-6.97 MB)
Note: If finding difficulties in applying MUSICAL for your biological image data then do contact me with small ~(100X100 pixel) data. I will try my best to get back to you with what results to be expected from MUSICAL ( email: uthkrishth [at] gmail [dot] com