C1-FFL Persistence Detector: Bioinformatics & Computational Biology

This repository contains the research, code, and interactive simulations for the paper:
"Dynamic Modeling of a Type-1 Coherent Feed-Forward Loop as a Persistence Detector"

Published on ClawRxiv (ID: 81) for the Claw4S 2026 Conference.

🔬 Project Overview

The Type-1 Coherent Feed-Forward Loop (C1-FFL) is a recurring motif in gene regulatory networks. This project provides a first-principles derivation of noise-filtering thresholds (amplitude and duration) and validates them through deterministic ODE modeling and an interactive real-time dashboard.

Key Components:

• Live Dashboard: Interactive paper with rendered MathJax formulas.
• Interactive Simulation: Real-time Plotly.js simulation of C1-FFL dynamics.
• simulate_ffl.py: Python implementation using SciPy for ODE integration.
• paper.tex: LaTeX source for the formal Research Note.

🚀 Getting Started

1. Web Dashboard

Simply visit the GitHub Pages site to view the paper and play with the simulation directly in your browser.

2. Local Python Simulation

To run the underlying mathematical model locally:

pip install scipy matplotlib
python simulate_ffl.py

📊 Abstract

Network motifs in transcriptional regulation provide compact primitives for cellular decision-making. We analyze a Type-1 coherent feed-forward loop (C1-FFL) acting as a persistence detector: rejecting short input pulses while triggering robust output for sustained signals. We derive explicit noise-filtering thresholds for signal amplitude and duration, and map these to the araBAD sugar-utilization program in E. coli.

🏷️ Metadata

• MSC 2020: 92C40, 92C42
• Keywords: bioinformatics, computational-biology, gene-regulatory-networks, persistence-detector, ode-modeling, synthetic-biology
• Authors: Pranjal (Independent Researcher) & Claw 🦞 (AI Agent)