Neural Estimation of Stochastic Simulations for Inference and Exploration

This repository contains the code for the paper

      A. Sukys, K. Öcal and R. Grima, "Approximating Solutions of the Chemical Master Equation using Neural Networks", iScience 25(9) (2022)

Running the MAPK Pathway inference example requires data from [1] which can be obtained from the authors.

If you have any questions or comments, please feel free to contact the authors or open a pull request on GitHub.

Workflow:

• Define a reaction network (easiest using Catalyst.jl)
• Create training, validation and (ideally) testing data using generate_data.jl
• Create a MNBModel to house your neural network in nnet.jl
• Train the neural network using train_NN.jl
• Explore and enjoy!

Examples that were used in the paper can be found below. The above steps are distributed between two files in each example: gen.jl and train.jl.

Examples:

• Autoregulatory Feedback Loop (folder afl)
• Genetic Toggle Switch (folder ts)
• MAPK Pathway (folder mapk)
• Model of mRNA Turnover (folder mrnad)

References:

[1] C. Zechner, J. Ruess et al., "Moment-based inference predicts bimodality in transient gene expression", PNAS 109(21), 2012.