pybool

A Python package to infer Boolean regulatory networks

Introduction

pybool is a Python package that infers Boolean regulatory networks from temporal expression constraints.

Consider the common scenario of a biologist who is studying a particular regulatory network. They study a set of genes that are known to play a role in the network. They have some background knowledge of particular regulatory connections from his own studies or from the literature. In addition to this they have perturbation data that reveals the temporal order of expression of the genes under some conditions. For example, these could be derived from loss-of-function or over-expression experiments. The biologist would like to elucidate the entire network and to this end can perform various experiments to test particular regulatory connections. These experiments are costly and time-consuming. Which connections should they focus on? This is where the pybool package can help. By modelling candidate regulatory networks using Boolean logic, pybool evaluates which networks are consistent with the perturbation data and the known regulatory connections.

To install pybool please read the installation instructions.

To learn more about how to use pybool please read the section on running pybool and the section on configuring pybool.

License

pybool is free for academic use. For commercial licenses please contact the author:

John Reid,
MRC Biostatistics Unit,
Institute of Public Health,
University Forvie Site,
Robinson Way,
Cambridge.
CB2 0SR.

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