cyclic-gmispy 0.3.3

A Python package for calculating Genetic Minimal Intervention Sets (gMIS) in metabolic networks with regulatory cycles

cyclic-gMISpy

A Python package for calculating Genetic Minimal Intervention Sets (gMIS) and Minimal Cut Sets (MCS) in metabolic networks with regulatory cycles.

Overview

cyclic-gMISpy is a computational tool designed for identifying minimal genetic interventions in metabolic networks that consider regulatory cycles and gene-protein-reaction (GPR) rules. The package extends traditional minimal cut set analysis by incorporating regulatory network dynamics and cyclic dependencies.

Features

• Minimal Cut Set (MCS) Calculation: Find minimal sets of reactions that disrupt metabolic objectives
• Genetic Minimal Intervention Sets (gMIS): Identify minimal gene knockouts considering GPR rules
• Regulatory Cycles Support: Handle cyclic dependencies in gene regulatory networks
• Parallel Computing: Multi-threaded calculations for improved performance
• Multiple Solvers: Support for Gurobi and CPLEX optimization solvers

Installation

Prerequisites

• Python ≥ 3.7
• COBRApy
• NumPy
• SciPy
• pandas
• tqdm
• bidict
• bonesis
• mpbn

Required Optimization Solvers

At least one of the following optimization solvers:

• Gurobi (recommended for performance)
• CPLEX

Install Package

# Clone the repository
git clone https://github.com/your-username/cyclic-gMISpy.git
cd cyclic-gMISpy

# Install dependencies
pip install -r requirements.txt

# Install the package
pip install -e .

Or use pip install via piptest

pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ cyclic-gmispy

Quick Start

Basic MCS Calculation

import cobra
from cyclic_gmis import calculateMCS

# Load your metabolic model
model = cobra.io.read_sbml_model("your_model.xml")

gMIS with Regulatory Cycles

import pandas as pd
from cyclic_gmis import calculateGMIS

# Load metabolic model
model = cobra.io.read_sbml_model("your_model.xml")

# Load regulatory network data
regulatory_df = pd.read_csv("regulatory_network.csv")

from cyclic_gmis import calculateParallelGMIS

# Run parallel gMIS calculation
parallel_results = calculateParallelGMIS(
    cobraModel=model,
    regulatory_dataframe=regulatory_df,
    numWorkers=8,
    maxKOLength=3
)

Core Components

Main Functions

• calculateParallelGMIS(): Calculate genetic minimal intervention sets with regulatory cycles
• calculateReadjustmentParallel(): Calculate readjustment cycles efficiently

Utilities

• buildGMatrix(): Build gene-protein-reaction matrix
• checkGMCS(): Validate computed genetic minimal cut sets
• saveSolutions(): Save results in various formats
• setSolver(): Configure optimization solver settings

Problem Definitions

• Support for different optimization problem formulations
• Flexible constraint handling
• Multiple objective functions

Configuration Options

Input Data Formats

Metabolic Models

• SBML format (via COBRApy)
• JSON format
• MAT files

Regulatory Networks

• CSV files with regulator-target relationships
• Tab-separated files
• Custom pandas DataFrame format

Citing

If you use cyclic-gMISpy in your research, please cite:

[Pending]

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Support

For questions and support:

• Open an issue on GitHub
• Contact: [[e-mail]]

Acknowledgments

• COBRApy community for metabolic modeling tools
• Bonesis framework for regulatory network analysis
• Optimization solver providers (Gurobi, CPLEX, SCIP)