| <!DOCTYPE html> |
| <html lang="en"> |
| <head> |
| <meta charset="UTF-8"> |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> |
| <title>ProcessDSL + FlowCell-10 Proposal</title> |
| <style> |
| body { |
| font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; |
| line-height: 1.6; |
| max-width: 800px; |
| margin: 0 auto; |
| padding: 20px; |
| background-color: #f8f9fa; |
| } |
| .container { |
| background: white; |
| padding: 40px; |
| border-radius: 8px; |
| box-shadow: 0 2px 10px rgba(0,0,0,0.1); |
| } |
| h1 { |
| color: #1f77b4; |
| text-align: center; |
| border-bottom: 3px solid #1f77b4; |
| padding-bottom: 10px; |
| } |
| h2 { |
| color: #1f77b4; |
| margin-top: 30px; |
| border-left: 4px solid #1f77b4; |
| padding-left: 15px; |
| } |
| h3 { |
| color: #ff7f0e; |
| margin-top: 25px; |
| } |
| .highlight { |
| background-color: #e6f3ff; |
| padding: 15px; |
| border-radius: 5px; |
| border-left: 4px solid #1f77b4; |
| margin: 20px 0; |
| } |
| .code-block { |
| background-color: #f8f9fa; |
| border: 1px solid #e9ecef; |
| border-radius: 5px; |
| padding: 15px; |
| font-family: 'Courier New', monospace; |
| font-size: 14px; |
| overflow-x: auto; |
| margin: 15px 0; |
| } |
| .flowchart-container { |
| text-align: center; |
| margin: 30px 0; |
| padding: 20px; |
| background-color: #f8f9fa; |
| border-radius: 8px; |
| } |
| .flowchart-container img { |
| max-width: 100%; |
| height: auto; |
| border: 1px solid #dee2e6; |
| border-radius: 5px; |
| } |
| ul { |
| padding-left: 20px; |
| } |
| li { |
| margin: 8px 0; |
| } |
| .benefit-box { |
| background-color: #fff4e6; |
| border: 1px solid #ff7f0e; |
| border-radius: 5px; |
| padding: 15px; |
| margin: 15px 0; |
| } |
| </style> |
| </head> |
| <body> |
| <div class="container"> |
| <h1>ProcessDSL + FlowCell-10 Proposal</h1> |
| |
| <div class="highlight"> |
| <p><strong>This proposal outlines a pilot initiative to integrate the "genome as program" concept and cellular process flowcharting into the Virtual Cell project.</strong> The goal is to formalize biological processes as executable, interpretable programs that can be learned, simulated, and manipulated by AI.</p> |
| </div> |
|
|
| <h2>1. ProcessDSL Specification</h2> |
| <p><strong>ProcessDSL</strong> is a domain-specific language for representing cellular processes. It compiles human-readable flowcharts into machine-executable forms such as stochastic rule systems, Petri nets, or hybrid ODE/event simulators.</p> |
| |
| <h3>Key features:</h3> |
| <ul> |
| <li>Reactions as rules with explicit guards and rate constants.</li> |
| <li>Conditional logic (IF/ELSE) for regulation.</li> |
| <li>Iterative loops (WHILE) for cyclic processes.</li> |
| <li>Event triggers for environmental or signaling changes.</li> |
| <li>Support for compartments (nucleus, cytosol, organelles).</li> |
| </ul> |
|
|
| <h2>2. FlowCell-10 Pilot Dataset</h2> |
| <p><strong>FlowCell-10</strong> is a curated set of ten well-characterized yeast pathways, each represented as:</p> |
| <ul> |
| <li>A canonical flowchart</li> |
| <li>A ProcessDSL file</li> |
| <li>Reference simulation outputs from literature data</li> |
| </ul> |
|
|
| <h3>Example pathways:</h3> |
| <ol> |
| <li>Glycolysis</li> |
| <li>TOR nutrient sensing pathway</li> |
| <li>Heat shock response</li> |
| <li>Autophagy initiation</li> |
| <li>Unfolded protein response (UPR)</li> |
| <li>Cell cycle G1/S transition</li> |
| <li>Mitochondrial respiration control</li> |
| <li>Amino acid biosynthesis regulation</li> |
| <li>Gluconeogenesis</li> |
| <li>Alcoholic fermentation</li> |
| </ol> |
|
|
| <h2>3. Example ProcessDSL (Glycolysis)</h2> |
| <div class="code-block"> |
| process Glycolysis in Cytosol: |
| state: [Glucose, G6P, F6P, F16BP, G3P, DHAP, PEP, Pyruvate, ATP, ADP, NAD+, NADH] |
| rule Hexokinase: Glucose + ATP -> G6P + ADP [guard: ATP>θ1] |
| rule PFK: F6P + ATP -> F16BP + ADP [guard: ATP<θ2 & AMP>θ3] |
| rule Aldolase: F16BP -> G3P + DHAP |
| rule TPI: DHAP <-> G3P |
| rule PyruvateKinase: PEP + ADP -> Pyruvate + ATP [allosteric: F16BP activates] |
| event GlucosePulse(t=0..T): inflow rate r_in |
| </div> |
|
|
| <h2>4. Expanded Glycolysis Flowchart</h2> |
| <p>Below is an example from FlowCell-10 showing <strong>Glycolysis in Yeast</strong> with branch and loop structure:</p> |
| |
| <div class="flowchart-container"> |
| <img src="YeastFlowchart1.drawio.png" alt="Glycolysis Pathway in Yeast" style="max-width: 100%; height: auto;"> |
| </div> |
|
|
| <h2>5. Deliverables</h2> |
| <ul> |
| <li>ProcessDSL specification and parser.</li> |
| <li>FlowCell-10 diagrams, DSL files, and simulation benchmarks.</li> |
| <li>Jupyter notebook demo: diagram → ProcessDSL → simulation → data comparison.</li> |
| <li>Documentation for extending the dataset.</li> |
| </ul> |
|
|
| <h2>6. Benefits to the Virtual Cell Project</h2> |
| <div class="benefit-box"> |
| <ul> |
| <li>Provides an interpretable, executable representation of cellular processes.</li> |
| <li>Bridges molecular prediction tools (e.g., AlphaFold 3) to systems-level dynamics.</li> |
| <li>Enables counterfactual simulations and intervention planning.</li> |
| <li>Creates training data for AI models to learn biological program induction.</li> |
| </ul> |
| </div> |
|
|
| <div class="highlight"> |
| <p><strong>This proposal demonstrates how computational biology and artificial intelligence can converge to create interpretable, executable models of biological systems.</strong></p> |
| </div> |
| </div> |
| </body> |
| </html> |
