Published January 4, 2022
| Version v1
Dataset
Open
Supplementary files for Reconstructing Kinetic Models for Dynamical Studies of Metabolism using Generative Adversarial Networks, additional part 1
Authors/Creators
- 1. EPFL (Ecole Polytechnique Federale de Lausanne), Lausanne, Switzerland
Description
Supplementary files containing datasets needed to reproduce the results of the manuscript "Reconstructing Kinetic Models for Dynamical Studies of Metabolism using Generative Adversarial Networks" by S. Choudhury et al.
The code to use with these data and reproduce the manuscript results is available at https://github.com/EPFL-LCSB/rekindle and https://gitlab.com/EPFL-LCSB/rekindle. The execution of parts of this code is dependent on the SkimPy toolbox (https://github.com/EPFL-LCSB/skimpy). Refer to the readme files on the REKINDLE code repositories for more details.
- Temporal evolution of perturbations in non-linear ordinary differential equations
- ode_solutions_physiology1.zip - contains 100 subfolders, each subfolder containing the time-series evolution data of 1000 kinetic models parameterized by REKINDLE generated parameter sets for physiology 1, each of the 1000 models having a random perturbation.
The detailed instructions and the main body of the dataset is available here: https://zenodo.org/record/5803120
Files
ode_solutions_physiology1.zip
Additional details
Funding
- European Commission
- SHIKIFACTORY100 - Modular cell factories for the production of 100 compounds from the shikimate pathway 814408
- Swiss National Science Foundation
- Computational Methods for modeling and analysis of large-scale metabolic networks 315230_163423
- European Commission
- PAcMEN - Predictive and Accelerated Metabolic Engineering Network 722287