If your quantifications involve something as simple as a perimeter, it may differ depending on your choice of #BioImageAnalysis platform. If you use Fiji your results will be different from your colleagues who use #Python or MATLAB 🧵 biorxiv.org/content/10.110…

Overall focus on #GUI in #BioImageAnalysis left little space to focus on numbers while making the workflows hard to integrate with modern day #DataScience! We proposed to go back to Object Oriented Programming and leave #GUI to Project Jupyter

Project Jupyter What you see here is a fluorescent #virological #plaque of OC43 common #coronavirus. It represents a result of virus spread from a single infected cell to its neighbours - an event horizon of #virology. #PyPlaque was built to measure these

Project Jupyter These are #virological #plaques of #Vaccinia virus (a prototypic #poxvirus) obtained from a commonly used crystal violet assay rather than a microscope. #PyPlaque can deal with that too, but for better performance external #ML model can be added

Project Jupyter Or in other words, MicrobeTV we've got Plaques!

Project Jupyter MicrobeTV Importantly we believe that our design pattern can be applied to other #BioImageAnalysis workflows. Our work is open source: contribute via a pull requests or fork it into your own repo Vardan Andriasyan Trina De github.com/plaque2/PyPlaq…