SMART ESTIMATION OF PARAMETERS IN REACTION NETWORKS (SMARTE)

Core Concepts

• A factor is something that is changed in an experiment, such as start concentration of a species and algorithm for parameter estimation.
• A level for a factor is a value that is assigned the factor for an experiment.
• Factor space has dimensions of factors, and the coordinates for a factor are its levels.
• A condition is a collection of pairs factor and level.
• A work unit is a collection of conditions. Typically, conditions are chosen as a hypercube in factor space.

Repository Structure

• docs - sphinx documentation
• tools - standalone scripts
• smarte - project code

Developer notes

• Use python3.9 (since there's a Tellurium problem with 3.10)
• Some iconfiguration may be required to use Jupyter.
• To get plots, sudo apt install python3.9-tk
• You should clone the following projects and include them in PYTHONPATH *`git clone https://github.com/ModelEngineering/fitterpp.git
  • git clone https://github.com/ModelEngineering/SBMLModel.git
• To get tkinter, sudo apt-get install python3.6-tk.
• Issues with Tellurium make it so that python 3.6 or 3.7 are required. Proceed as follows on macos
  • install homebrew: /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
  • Use homebrew to install pyenv (manages versions of python): brew updae; brew install pyenv
  • pyenv install 3.7.10
  • make 3.7.10 the default pyenv version: pyenv global 3.7.10
  • creae the virtual environment: pyenv exec python -m venv smt
  • source smt/bin/activate
  • pip install --upgrade pip # upgrade the version of pip
  • pip install -r requirements.txt

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