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Supplementary material for CPT tutorial on logic modeling for quantitative systems pharmacology
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CellNOptR_optimisation.R
LICENSE
PriorKnowledgeNetwork.sif
README.md
logicODEparameters_edges.txt
logicODEparameters_nodes.txt
network_extension.docx
perturbationData_LNCaP_MIDAS.csv
pypath_code.py
table_epistasis.xlsx
table_survivalprobas.xlsx
trainedmodel.bnd
trainedmodel.cfg

README.md

CPT_QSPtutorial

Supplementary material for the CPT tutorial paper:

Title: Logic modeling in quantitative systems pharmacology

Authors: Pauline Traynard*1, Luis Tobalina*2, Federica Eduati*3, Laurence Calzone1, Julio Saez-Rodriguez2,3

* Co-first authors

Affiliations: 1 Institut Curie, PSL Research University, Mines Paris Tech, Inserm, U900, F-75005, Paris, France. 2 RWTH Aachen University, Faculty of Medicine, Joint Research Centre for Computational Biomedicine, MTI2 Wendlingweg 2 D-52074 Aachen 3 European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus CB10 1SD Hinxton

##Included files

#####Construction of Prior Knowledge Network: pypath_code.py Python code for pypath

network_extension.docx Description of step-by-step model extension using pypath

PriorKnowledgeNetwork.sif Final Prior Knowledge Network (PKN)

#####Model training perturbationData_LNCaP_MIDAS.csv Perturbation data from (Lescarbeau et al., 2014) normalised and in MIDAS format

CellNOptR_optimisation.R R code for optimisation with CellNOptR logic ODE

#####Trained model: trainedmodel.bnd

trainedmodel.cfg

logicODEparameters_edges.txt

logicODEparameters_nodes.txt

#####MaBoSS simulations and genetic interactions: table_survivalprobas.xlsx table_epistasis.xlsx

##License This project is licensed under the terms of GPLv3.

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