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<title>About GLMP — Genome Logic Modeling Project</title> |
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<h1>🧬 About GLMP</h1> |
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<div class="subtitle">Genome Logic Modeling Project — Computational Biology Research</div> |
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<a href="index.html">← Back to Database</a> |
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<h2>Project Overview</h2> |
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<p>The <strong>Genome Logic Modeling Project (GLMP)</strong> represents a systematic approach to understanding biological processes as computational programs. By applying programming framework methodologies to biological systems, we reveal the underlying logical architecture that governs cellular decision-making.</p> |
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<p>Our research has identified a conserved computational pattern across 108 biological processes: the <strong>100:11:6:2 architecture</strong>, representing the ratio of sequential conditionals to OR gates to AND gates to NOT gates. This discovery suggests that evolution has optimized biological systems for efficiency, robustness, integration, and control.</p> |
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<div class="stat-number">108</div> |
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<div class="stat-label">Biological Processes</div> |
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<div class="stat-number">7,152</div> |
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<div class="stat-label">Total Nodes</div> |
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<div class="stat-number">100:11:6:2</div> |
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<div class="stat-label">Computational Architecture</div> |
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<div class="stat-number">3</div> |
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<div class="stat-label">Model Organisms</div> |
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<h2>Key Publications</h2> |
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<div class="paper-title">"The 100:11:6:2 Pattern: Evidence for a Conserved Computational Architecture in Prokaryotic and Eukaryotic Core Processes"</div> |
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<div class="paper-description"> |
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<strong>Welz, G. (2025)</strong> — Comprehensive analysis of ~7,000 computational nodes across 108 biological processes reveals evolution's optimization for efficiency, robustness, integration, and control. This work demonstrates that biological regulatory processes implement computable Boolean logic expressible as formal mathematical formulas. |
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<div class="paper-title">"The Programming Framework: A Universal Method for Process Analysis Using LLMs and Visual Flowcharts"</div> |
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<strong>Welz, G. (2025)</strong> — Introduces the meta-tool underlying GLMP, demonstrating how large language models can systematically convert natural language descriptions of biological processes into structured computational visualizations. |
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<div class="paper-title">"From Inspiration to AI: Biology as Visual Programming"</div> |
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<strong>Welz, G. (2025)</strong> — Explores the conceptual foundation for viewing genomes as computational programs, building upon early insights from 1995 with modern visualization and analysis tools. |
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<h2>Methodology</h2> |
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<p>GLMP employs a standardized eight-category color-coding system to represent biological processes as computational programs:</p> |
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<ul> |
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<li><strong>Green:</strong> Environmental Triggers & Input Signals</li> |
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<li><strong>Amber/Gold:</strong> Enzymes & Catalytic Proteins</li> |
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<li><strong>Dark Sky Blue:</strong> Chemical Processing & Reactions</li> |
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<li><strong>Light Cyan:</strong> Intermediate States & Molecules</li> |
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<li><strong>Yellow 🟡:</strong> OR Logic Gates (Decision Points)</li> |
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<li><strong>Purple 🟣:</strong> AND Logic Gates (Integration)</li> |
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<li><strong>Red 🔴:</strong> NOT Logic Gates (Repression/Inhibition)</li> |
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<li><strong>Black:</strong> Final Products & Outputs</li> |
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</ul> |
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<h2>Research Impact</h2> |
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<p>Our findings suggest that non-coding DNA may encode logical formulas through the spatial arrangement of regulatory elements, implementing Boolean circuits in genomic sequence. This represents a testable hypothesis that invites experimental validation by the research community.</p> |
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<p>The complete dataset of 108 processes with comprehensive citations is publicly available through our interactive database, enabling researchers to validate findings, explore computational patterns, and test proposed hypotheses through experimental approaches.</p> |
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<h3>Contact Information</h3> |
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<p><strong>Gary Welz</strong><br> |
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Principal Investigator, Genome Logic Modeling Project<br> |
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Department of Mathematics and Computer Science<br> |
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John Jay College of Criminal Justice, City University of New York (CUNY)<br> |
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<strong>Email:</strong> gwelz@jjay.cuny.edu<br> |
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<strong>GitHub:</strong> <a href="https://github.com/garywelz" target="_blank" rel="noopener">github.com/garywelz</a><br> |
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<strong>Hugging Face:</strong> <a href="https://huggingface.co/garywelz" target="_blank" rel="noopener">huggingface.co/garywelz</a></p> |
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