What is Pasmopy?
Pasmopy is a scalable toolkit to identify prognostic factors for cancers based on intracellular signaling dynamics generated from personalized kinetic models. It is compatible with biomass and offers the following features:
Construction of mechanistic models from text
Personalization of the model using transcriptome data
Prediction of patient outcome based on in silico signaling dynamics
Sensitivity analysis for prediction of potential drug targets
If you use Pasmopy in a scientific publication, please cite the following paper:
Imoto, H., Yamashiro, S. & Okada, M. A text-based computational framework for patient -specific modeling for classification of cancers. iScience 25, 103944 (2022). https://doi.org/10.1016/j.isci.2022.103944
If you discovered an error or need help, please contact me via GitHub Issues. Please head over to GitHub Discussions if you have any questions or would like to start a new discussion. In either case, you can also always send me an email.
Any contributions to Pasmopy are more than welcome!