Skip to content

Sparse, efficient, non-ODE approximation for biochemical signaling

License

Notifications You must be signed in to change notification settings

BhallaLab/HillTau

Repository files navigation

alt text

HillTau

Sparse, efficient, non-ODE approximation for biochemical signaling

Copyright (C) Upinder S. Bhalla and NCBS-TIFR, 2020

Contents of this repository:

README.md: this file

LICENSE: License terms. GPL 3.0.

PythonCode: The code to run HillTau.

CppCode: The code to run HillTau using python bindings via Pybind11 to C++.

MASH: Model Abstraction from SBML to HillTau. Utility program for model reduction, see

Documentation for MASH

ht2sbml: Utility program to convert HillTau (JSON format) model to a near- approximation in SBML, suitable for running on several ODE simulators like COPASI.

htgraph: Utility program to generate png or svg graphs to display reaction structure of HillTau model.

HillTau

Documentation for HillTau

The following paper discusses design and examples in detail:

HillTau: A fast, compact abstraction for model reduction in biochemical signaling networks.
Bhalla US.
PLoS Comput Biol. 2021

DOI

Installation

Simple and slow Python version: Copy the two files hillTau.py and hillTauSchema.json from PythonCode to your target directory.
If you want to run the utilities, also copy mash.py, ht2sbml.py and htgraph.py to the target directory.

Complex and fast C++ version: pip install hillTau
This will help install the much faster C++ version of HillTau, with the same friendly Python interface.

Limitations:

  1. The pip install version has only been configured for Linux systems. Mac will come soon, and Windows is a work in progress.

  2. The htgraph.py script requires a separate installation of GraphViz. This may be done on Linux systems using sudo apt-get install GraphViz

  3. The mash.py script requires a separate installation of the MOOSE development branch. This may be done on Linux systems by accessing the GitHub website for MOOSE, checking it out, and compiling as per the instructions in INSTALL.md

    git clone https://github.com/BhallaLab/moose-core.git

Once the pip install is done, you can use import hillTau in any python script where you need it.
You can also run the standalone hillTau code from the command line like this:

hillTau model_file <arguments>

Tested on::

  • Ubuntu 20.x
  • CentOS el7
  • More to come soon.

Versions

The Python version of HillTau has been tested with Python 2.7.17 and Python 3.6.9
The C++ version of HillTau uses Python 3.6 or higher. It is the recommended version.

Examples

Examples: Directory with examples

Examples/HT_MODELS: Examples of HillTau models

Examples/KKIT_MODELS: Examples of KKIT models which map to the HillTau ones. KKIT models are an old ODE biochemical model format compatible with GENESIS and MOOSE.

Examples/SBML_MODELS: Examples of SBML models which map to the HillTau ones. SBML is the Systems Biology Markup Language and is a standard for defining many kinds of systems biology models, including the current mass-action ones.

Examples/PaperFigures: Using the HillTau form to generate the figures for the reference paper for HillTau. Most of these require MOOSE to be installed, but fig1.py just requires HillTau.

Other projects and papers that relate to HillTau: Resources.md

About

Sparse, efficient, non-ODE approximation for biochemical signaling

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages