RMut

RMut performs sensitivity analysis of Boolean network models as an R package, evaluating effects of node-based, edgetic, and user-defined mutations to assess network robustness.

Key Features:

• Comprehensive Mutation Analysis: Supports node-based mutations (overexpression, state-flip) and edgetic mutations (edge-addition, edge-reversal, edge-removal), and accepts user-defined mutations.
• Customizable Parameters: Allows specification of mutation area and duration time within the network for targeted sensitivity analyses.
• Parallel Processing Capability: Implements a parallel algorithm using the OpenCL library to accelerate analysis of large-scale Boolean networks.

Scientific Applications:

• Biological Network Sensitivity: Applied to real biological networks to reveal sensitivity to overexpression/state-flip and edge-addition/edge-reversal mutations.
• Drug Target Prediction: Used to compare node-based and edgetic mutations for drug target prediction, with edgetic mutations showing superior predictive power.
• Synergistic Mutation Effects: Employed to analyze double edge-removal mutations and detect synergistic impacts on network sensitivity.

Methodology:

Uses Boolean network models and a parallel computing implementation via OpenCL.