scholarly journals PYMEVisualize: an open-source tool for exploring 3D super-resolution data

2020 ◽  
Author(s):  
Zach Marin ◽  
Michael Graff ◽  
Andrew E. S. Barentine ◽  
Christian Soeller ◽  
Kenny Kwok Hin Chung ◽  
...  

ABSTRACTLocalization-based super-resolution microscopy techniques such as PALM, STORM, and PAINT are increasingly critical tools for biological discovery. These methods generate lists of single fluorophore positions that capture nanoscale structural details of subcellular organisation, but to develop biological insight, we must post-process and visualize this data in a meaningful way. A large number of algorithms have been developed for localization post-processing, transforming point data into representations which approximate traditional microscopy images, and performing specific quantitative analysis directly on points. Implementations of these algorithms typically stand in isolation, necessitating complex workflows involving multiple different software packages. Here we present PYMEVisualize, an open-source tool for the interactive exploration and analysis of 3D, multicolor, single-molecule localization data. PYMEVisualize brings together a broad range of the most commonly used post-processing, density mapping, and direct quantification tools in an easy-to-use and extensible package. This software is one component of the PYthon Microscopy Environment (python-microscopy.org), an integrated application suite for light microscopy acquisition, data storage, visualization, and analysis built on top of the scientific Python environment.

Author(s):  
Sachin Arun Thanekar ◽  
K. Subrahmanyam ◽  
A.B. Bagwan

<p>Nowadays we all are surrounded by Big data. The term ‘Big Data’ itself indicates huge volume, high velocity, variety and veracity i.e. uncertainty of data which gave rise to new difficulties and challenges. Hadoop is a framework which can be used for tremendous data storage and faster processing. It is freely available, easy to use and implement. Big data forensic is one of the challenges of big data. For this it is very important to know the internal details of the Hadoop. Different files are generated by Hadoop during its process. Same can be used for forensics. In our paper our focus is on digital forensics and different files generated during different processes. We have given the short description on different files generated in Hadoop. With the help of an open source tool ‘Autopsy’ we demonstrated that how we can perform digital forensics using automated tool and thus big data forensics can be done efficiently.</p>


2017 ◽  
Author(s):  
Hazen P. Babcock

ABSTRACTIn this work we explore the use of industrial grade CMOS cameras for single molecule localization microscopy (SMLM). We show that the performance of these cameras in single imaging plane SMLM applications is comparable to much more expensive scientific CMOS (sCMOS) cameras. We show that these cameras can be used in more demanding biplane, multiplane and spectrally resolved SMLM applications. The 10-40× reduction in camera cost makes it practical to build SMLM setups with 4 or more cameras. In addition we provide open-source software for simultaneously controlling multiple CMOS cameras and for the reduction of the movies that are acquired to super-resolution images.


2021 ◽  
Author(s):  
Michael J Wester ◽  
David J Schodt ◽  
Hanieh Mazloom-Farsibaf ◽  
Mohamadreza Fazel ◽  
Sandeep Pallikkuth ◽  
...  

We describe a robust, fiducial-free method of drift correction for use in single molecule localization-based super-resolution methods. The method combines periodic 3D registration of the sample using brightfield images with a fast post-processing algorithm that corrects residual registration errors and drift between registration events. The method is robust to low numbers of collected localizations, requires no specialized hardware, and provides stability and drift correction for an indefinite time period.


2020 ◽  
Author(s):  
Pedro M. Pereira ◽  
Nils Gustafsson ◽  
Mark Marsh ◽  
Musa M. Mhlanga ◽  
Ricardo Henriques

Localization based super-resolution microscopy relies on the detection of individual molecules cycling between fluorescent and non-fluorescent states. These transitions are commonly regulated by high-intensity illumination, imposing constrains to imaging hardware and producing sample photodamage. Here, we propose single-molecule self-quenching as a mechanism to generate spontaneous photoswitching independent of illumination. To demonstrate this principle, we developed a new class of DNA-based open-source Super-Resolution probes named Super-Beacons, with photoswitching kinetics that can be tuned structurally, thermally and chemically. The potential of these probes for live-cell friendly Super-Resolution Microscopy without high-illumination or toxic imaging buffers is revealed by imaging Interferon Inducible Transmembrane proteins (IFITMs) at sub-100nm resolutions.


2015 ◽  
Vol 11 (1) ◽  
pp. 67-91 ◽  
Author(s):  
Jennifer Day ◽  
Yiqun Chen ◽  
Peter Ellis ◽  
Mark Roberts

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Michael J. Wester ◽  
David J. Schodt ◽  
Hanieh Mazloom-Farsibaf ◽  
Mohamadreza Fazel ◽  
Sandeep Pallikkuth ◽  
...  

AbstractWe describe a robust, fiducial-free method of drift correction for use in single molecule localization-based super-resolution methods. The method combines periodic 3D registration of the sample using brightfield images with a fast post-processing algorithm that corrects residual registration errors and drift between registration events. The method is robust to low numbers of collected localizations, requires no specialized hardware, and provides stability and drift correction for an indefinite time period.


2021 ◽  
Author(s):  
Zach Marin ◽  
Michael Graff ◽  
Andrew E. S. Barentine ◽  
Christian Soeller ◽  
Kenny Kwok Hin Chung ◽  
...  

2020 ◽  
pp. 100001
Author(s):  
Wilko Heitkoetter ◽  
Bruno U. Schyska ◽  
Danielle Schmidt ◽  
Wided Medjroubi ◽  
Thomas Vogt ◽  
...  

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