PDIpy 0.0.4

Simulate Photodynamic Inactivation (PDI) of a Cocci Bacterium from a kinetics model of membrane oxidation.

Antibiotic resistance is developing medical crisis that is projected to surpass cancer in annual deaths by mid-21st century. Photodynamic Inactivation (PDI) is a promising treatment method that escapes resistance evolution and may be an essential technology to hamper the growing threat of resistant pathogens. The requisite rate of research to mitigate these somber projections requires computational tools that can improve and expedite experimental research in developing PDI treatments.

PDIpy is offered as the first comprehensive software of PDI to fulfill this by simulating PDI biochemistry from a chemical kinetics model. PDIpy accepts user inputs of an experimental system, executes a Tellurium kinetic system, and expresses and exports the results through CSV spreadsheets and SVG images. Post-processing of the simulation data is further supported with a function that parses the based upon user parameters. The examples directory of the PDIpy GitHub exemplifies PDIpy through replicating experimental observations. Users and developers are encouraged to critique and improve PDIpy, as an open-source library, through GitHub issues.

Installation

pdipy is installed in a command prompt, Powershell, Terminal, or Anaconda Command Prompt via pip:

pip install pdipy

The full documentation is provided by ReadTheDocs.