Usage

📝 Overview

Gitsbe takes a general Boolean network topology together with cell-line-specific training data (produced by Celios) and evolves an ensemble of Boolean models whose attractors match observed steady-state behaviour.

The genetic algorithm explores the space of possible logic rules for each node in the network, selecting those parameterisations that best reproduce the training profile.

🔄 Workflow within TRAFIKK

1. 📥 Input: General signalling network (.sif) + cell-line training data from Celios

2. ⚙️ Process: Genetic-algorithm-based model parameterisation

3. 📦 Output: Ensemble of Boolean models (.zip) used by Oris

⚙️ Configuration

Gitsbe is configured via property files that control the genetic algorithm parameters (population size, mutation rate, number of generations, etc.) and input/output paths.

For detailed configuration options and usage examples, see the Gitsbe documentation.

🔗 Source code

The source code is available at github.com/druglogics/gitsbe.