Fix: Remove unused plotly/numpy imports

app.py

@@ -1,1038 +1,1036 @@
-"""
-TopoGrammar - Grammar-Aware 3D Genome Engine Demo
-==================================================
-
-Hugging Face Spaces Demo for TopoGrammar v2.1.0
-The Industry's First Grammar-Aware Engine for Balanced Structural Variants
-
-Copyright (c) 2026 Bryan Daugherty, Gregory Ward & Shawn Ryan. All Rights Reserved.
-
-This demo showcases TopoGrammar's capabilities without exposing proprietary algorithms.
-All results are pre-computed demonstrations for educational purposes.
-"""
-
-import gradio as gr
-import hashlib
-import random
-import time
-import httpx
-import json
-import os
-from datetime import datetime
-from typing import Optional, Dict, List, Tuple
-import plotly.graph_objects as go
-import numpy as np
-
-# =============================================================================
-# BSV Blockchain Configuration
-# =============================================================================
-
-BSV_API_URL = "https://simplebsv.codenlighten.org"
-BSV_API_KEY = os.getenv("BSV_API_KEY")  # Set via HF Secrets
-
-
-def publish_to_bsv(data: Dict) -> Optional[str]:
-    """
-    Publish attestation data to BSV blockchain via SimpleBSV API.
-
-    Args:
-        data: Dictionary containing attestation data (no trade secrets)
-
-    Returns:
-        Transaction ID if successful, None otherwise
-    """
-    # Guard clause: fail gracefully if no key configured
-    if not BSV_API_KEY:
-        print("BSV_API_KEY not configured - running in offline mode")
-        return None
-    
-    try:
-        headers = {
-            "Content-Type": "application/json",
-            "x-api-key": BSV_API_KEY
-        }
-
-        # Use ?wait=true for synchronous response with txid
-        response = httpx.post(
-            f"{BSV_API_URL}/publish/json?wait=true",
-            headers=headers,
-            json={"json": data},
-            timeout=30.0
-        )
-
-        if response.status_code == 200:
-            result = response.json()
-            return result.get("txid")
-        else:
-            print(f"BSV API error: {response.status_code} - {response.text}")
-            return None
-
-    except Exception as e:
-        print(f"BSV publish error: {e}")
-        return None
-
-# =============================================================================
-# Demo Configuration - Pre-computed results (no trade secrets exposed)
-# =============================================================================
-
-# Demo VUS Examples with pre-computed classifications
-VUS_EXAMPLES = {
-    "brca1_boundary": {
-        "name": "BRCA1 TAD Boundary Disruption",
-        "variant_id": "chr17:43,044,295 G>A",
-        "gene": "BRCA1",
-        "initial_class": "VUS",
-        "final_class": "Pathogenic",
-        "confidence": 0.93,
-        "mechanism": "TAD Boundary Disruption",
-        "evidence_codes": ["PS3_insulation", "PM1_boundary", "PS3_ctcf"],
-        "insulation_change": -0.52,
-        "description": "This intronic variant disrupts a CTCF binding site at a critical TAD boundary, causing enhancer-promoter miscommunication affecting BRCA1 expression.",
-    },
-    "myc_enhancer_hijack": {
-        "name": "MYC Enhancer Hijacking",
-        "variant_id": "chr8:128,750,000 inv(500kb)",
-        "gene": "MYC",
-        "initial_class": "VUS",
-        "final_class": "Pathogenic",
-        "confidence": 0.89,
-        "mechanism": "Enhancer Hijacking",
-        "evidence_codes": ["PS3_neoloop", "PS2_oncogene", "PM1_boundary"],
-        "insulation_change": -0.68,
-        "description": "Balanced inversion creates a neo-loop connecting MYC to a hijacked super-enhancer, causing oncogene activation without copy number change.",
-    },
-    "sonic_hedgehog": {
-        "name": "SHH Limb Enhancer",
-        "variant_id": "chr7:156,584,000 del(50kb)",
-        "gene": "SHH",
-        "initial_class": "VUS",
-        "final_class": "Likely Pathogenic",
-        "confidence": 0.85,
-        "mechanism": "Enhancer Deletion",
-        "evidence_codes": ["PM1_regulatory", "PP3_conservation", "PS3_insulation"],
-        "insulation_change": -0.41,
-        "description": "Deletion removes the ZRS limb enhancer from SHH regulatory domain, disrupting developmental gene expression.",
-    },
-    "benign_intronic": {
-        "name": "Benign Intronic SNP",
-        "variant_id": "chr12:25,398,284 C>T",
-        "gene": "KRAS",
-        "initial_class": "VUS",
-        "final_class": "Benign",
-        "confidence": 0.91,
-        "mechanism": "No 3D Impact",
-        "evidence_codes": ["BS1_frequency", "BP4_no_disruption"],
-        "insulation_change": 0.02,
-        "description": "Deep intronic variant with no effect on TAD structure, CTCF binding, or regulatory grammar. Common in population databases.",
-    },
-    "tp53_scramble": {
-        "name": "TP53 Grammar Scrambling",
-        "variant_id": "chr17:7,670,000 inv(120kb)",
-        "gene": "TP53",
-        "initial_class": "VUS",
-        "final_class": "Pathogenic",
-        "confidence": 0.96,
-        "mechanism": "Regulatory Grammar Scrambling",
-        "evidence_codes": ["PS3_semantic", "PS3_insulation", "PM1_boundary", "PP3_conservation"],
-        "insulation_change": -0.71,
-        "description": "Balanced inversion scrambles the regulatory grammar of TP53, inverting enhancer-promoter orientation and disrupting tumor suppressor expression.",
-    },
-}
-
-# Demo TAD examples
-TAD_EXAMPLES = {
-    "chr21_dscr": {
-        "name": "Chromosome 21 - Down Syndrome Critical Region",
-        "region": "chr21:35,000,000-40,000,000",
-        "n_tads": 4,
-        "n_boundaries": 5,
-        "ctcf_sites": 12,
-        "genes": ["DSCR1", "DSCR3", "DSCR4", "RUNX1"],
-        "boundary_strength": [0.85, 0.92, 0.78, 0.88, 0.81],
-    },
-    "chr7_egfr": {
-        "name": "Chromosome 7 - EGFR Locus",
-        "region": "chr7:55,000,000-56,500,000",
-        "n_tads": 3,
-        "n_boundaries": 4,
-        "ctcf_sites": 8,
-        "genes": ["EGFR", "LANCL2", "VOPP1"],
-        "boundary_strength": [0.91, 0.87, 0.94, 0.82],
-    },
-    "chr8_myc": {
-        "name": "Chromosome 8 - MYC Oncogene",
-        "region": "chr8:127,500,000-129,500,000",
-        "n_tads": 2,
-        "n_boundaries": 3,
-        "ctcf_sites": 6,
-        "genes": ["MYC", "PVT1"],
-        "boundary_strength": [0.96, 0.89, 0.93],
-    },
-}
-
-# Demo Neo-Loop examples
-NEOLOOP_EXAMPLES = {
-    "burkitt_myc": {
-        "name": "Burkitt Lymphoma - MYC Translocation",
-        "sv_type": "Translocation t(8;14)",
-        "oncogene": "MYC",
-        "hijacked_enhancer": "IGH Super-Enhancer",
-        "loop_strength": 0.92,
-        "clinical_priority": "Critical",
-        "cancer_type": "Burkitt Lymphoma",
-        "description": "Classic t(8;14) translocation juxtaposes MYC with immunoglobulin heavy chain enhancers, creating pathogenic neo-loop.",
-    },
-    "ewing_ewsr1": {
-        "name": "Ewing Sarcoma - EWSR1-FLI1",
-        "sv_type": "Translocation t(11;22)",
-        "oncogene": "EWSR1-FLI1 fusion",
-        "hijacked_enhancer": "GGAA microsatellite enhancers",
-        "loop_strength": 0.88,
-        "clinical_priority": "Critical",
-        "cancer_type": "Ewing Sarcoma",
-        "description": "Fusion protein creates neo-loops at GGAA microsatellites, aberrantly activating developmental genes.",
-    },
-    "aml_runx1": {
-        "name": "AML - RUNX1 Disruption",
-        "sv_type": "Inversion inv(16)",
-        "oncogene": "CBFB-MYH11 fusion",
-        "hijacked_enhancer": "Myeloid enhancer cluster",
-        "loop_strength": 0.85,
-        "clinical_priority": "High",
-        "cancer_type": "Acute Myeloid Leukemia",
-        "description": "Pericentric inversion disrupts normal RUNX1 regulation, creating aberrant chromatin loops.",
-    },
-}
-
-# Benchmark comparisons
-BENCHMARK_DATA = {
-    "tad_detection": {
-        "TopoGrammar (CTCF-gated)": {"accuracy": 91, "f1": 0.91, "subtad": True},
-        "HiCCUPS": {"accuracy": 80, "f1": 0.76, "subtad": False},
-        "Arrowhead": {"accuracy": 78, "f1": 0.74, "subtad": False},
-        "TopDom": {"accuracy": 75, "f1": 0.71, "subtad": False},
-    },
-    "vus_resolution": {
-        "reclassification_rate": 68,
-        "pathogenic_accuracy": 93,
-        "mean_confidence": 87,
-    },
-    "insulation_density": {
-        "major_tads": 9.11,
-        "all_boundaries": 15.57,
-        "improvement": 70.9,
-    },
-}
-
-
-# =============================================================================
-# Visualization Functions
-# =============================================================================
-
-def create_contact_map_ascii(region: str, n_tads: int) -> str:
-    """Create ASCII representation of a Hi-C contact map with TADs."""
-    size = 40
-    map_lines = []
-
-    # Create diagonal pattern with TAD blocks
-    tad_size = size // n_tads
-
-    for i in range(size):
-        row = ""
-        for j in range(size):
-            if abs(i - j) <= 2:
-                row += "██"  # Diagonal
-            elif (i // tad_size) == (j // tad_size):
-                # Within same TAD
-                distance = abs(i - j)
-                if distance < tad_size // 2:
-                    row += "▓▓"
-                elif distance < tad_size:
-                    row += "░░"
-                else:
-                    row += "  "
-            else:
-                row += "  "
-        map_lines.append(row)
-
-    return "\n".join(map_lines)
-
-
-def create_insulation_profile(boundary_strengths: List[float]) -> str:
-    """Create ASCII insulation score profile."""
-    lines = []
-    lines.append("Insulation Score Profile:")
-    lines.append("=" * 60)
-
-    for i, strength in enumerate(boundary_strengths):
-        bar_len = int(strength * 40)
-        bar = "█" * bar_len + "░" * (40 - bar_len)
-        lines.append(f"Boundary {i+1}: [{bar}] {strength:.2f}")
-
-    lines.append("=" * 60)
-    return "\n".join(lines)
-
-
-def create_grammar_diagram(mechanism: str) -> str:
-    """Create regulatory grammar visualization."""
-    if mechanism == "Regulatory Grammar Scrambling":
-        return """
-┌─────────────────────────────────────────────────────────────┐
-│                  REGULATORY GRAMMAR ANALYSIS                 │
-├─────────────────────────────────────────────────────────────┤
-│                                                             │
-│  REFERENCE GRAMMAR:                                         │
-│  ┌──────┐   ┌──────────┐   ┌──────────┐   ┌──────┐        │
-│  │CTCF+ │ → │ ENHANCER │ → │ PROMOTER │ → │ GENE │        │
-│  └──────┘   └──────────┘   └──────────┘   └──────┘        │
-│  "The enhancer activates the gene"                         │
-│                                                             │
-│  VARIANT GRAMMAR (SCRAMBLED):                               │
-│  ┌──────┐   ┌──────────┐   ┌──────────┐   ┌──────┐        │
-│  │ GENE │ ← │ PROMOTER │ ← │ ENHANCER │ ← │CTCF- │        │
-│  └──────┘   └──────────┘   └──────────┘   └──────┘        │
-│  "Gene the activates enhancer the" ⚠ SCRAMBLED            │
-│                                                             │
-│  SEMANTIC BREAK SCORE: 0.85 (CRITICAL)                     │
-│  • Token Disruption: 30% weight                            │
-│  • Order Inversion: 40% weight                             │
-│  • Orientation Flip: 30% weight                            │
-│                                                             │
-└─────────────────────────────────────────────────────────────┘
-"""
-    elif mechanism == "Enhancer Hijacking":
-        return """
-┌─────────────────────────────────────────────────────────────┐
-│                   ENHANCER HIJACKING ANALYSIS                │
-├─────────────────────────────────────────────────────────────┤
-│                                                             │
-│  NORMAL TOPOLOGY:                                           │
-│  ┌─────────────────┐     ┌─────────────────┐               │
-│  │   TAD A         │     │   TAD B         │               │
-│  │ [Enhancer]──────│─X───│──────[Oncogene] │               │
-│  │      ↓          │     │                 │               │
-│  │  [Target Gene]  │     │                 │               │
-│  └─────────────────┘     └─────────────────┘               │
-│         BOUNDARY BLOCKS CONTACT                             │
-│                                                             │
-│  AFTER STRUCTURAL VARIANT:                                  │
-│  ┌──────────────────────────────────────────┐              │
-│  │              FUSED TAD                    │              │
-│  │ [Enhancer]═══════════════════[Oncogene]  │              │
-│  │      ↓ NEO-LOOP FORMED ↓                 │              │
-│  │  [Target Gene]  ⚠ ONCOGENE ACTIVATED ⚠   │              │
-│  └──────────────────────────────────────────┘              │
-│                                                             │
-│  LOOP STRENGTH: 0.89 | PRIORITY: CRITICAL                  │
-│                                                             │
-└─────────────────────────────────────────────────────────────┘
-"""
-    elif mechanism == "TAD Boundary Disruption":
-        return """
-┌─────────────────────────────────────────────────────────────┐
-│                TAD BOUNDARY DISRUPTION ANALYSIS              │
-├─���───────────────────────────────────────────────────────────┤
-│                                                             │
-│  NORMAL INSULATION:                                         │
-│  ████████████████ │ ████████████████                       │
-│      TAD A        │      TAD B                              │
-│                CTCF│CTCF                                    │
-│               ▲▲▲▲▲│▲▲▲▲▲                                   │
-│            Strong Boundary                                  │
-│                                                             │
-│  AFTER VARIANT (CTCF SITE DISRUPTED):                       │
-│  ████████████████   ████████████████                       │
-│      TAD A    ░░░░░░░   TAD B                              │
-│                 ↓↓↓↓↓                                       │
-│           Insulation Leak                                   │
-│                                                             │
-│  INSULATION CHANGE: -52%                                    │
-│  BOUNDARY LOSS: MAJOR                                       │
-│                                                             │
-└─────────────────────────────────────────────────────────────┘
-"""
-    else:
-        return """
-┌─────────────────────────────────────────────────────────────┐
-│                    3D GENOME ANALYSIS                        │
-├─────────────────────────────────────────────────────────────┤
-│                                                             │
-│  No significant 3D structural impact detected.              │
-│                                                             │
-│  • TAD boundaries: INTACT                                   │
-│  • Insulation scores: NORMAL                                │
-│  • Regulatory grammar: PRESERVED                            │
-│  • CTCF binding: UNAFFECTED                                 │
-│                                                             │
-└─────────────────────────────────────────────────────────────┘
-"""
-
-
-def create_confidence_bars(evidence_codes: List[str], confidence: float) -> str:
-    """Create evidence code visualization."""
-    lines = []
-    lines.append("\n### Evidence Summary\n")
-
-    for code in evidence_codes:
-        # Determine strength from code prefix
-        if code.startswith("PS"):
-            strength = "Strong"
-            bar = "████████████████████"
-            color = "🟢"
-        elif code.startswith("PM"):
-            strength = "Moderate"
-            bar = "████████████░░░░░░░░"
-            color = "🟡"
-        elif code.startswith("PP"):
-            strength = "Supporting"
-            bar = "████████░░░░░░░░░░░░"
-            color = "🟠"
-        elif code.startswith("BS") or code.startswith("BP"):
-            strength = "Benign"
-            bar = "████████████████████"
-            color = "🔵"
-        else:
-            strength = "Unknown"
-            bar = "░░░░░░░░░░░░░░░░░░░░"
-            color = "⚪"
-
-        lines.append(f"{color} **{code}** ({strength}): `{bar}`")
-
-    lines.append(f"\n**Overall Confidence**: {confidence:.0%}")
-
-    return "\n".join(lines)
-
-
-def generate_bsv_attestation(variant_id: str, classification: str, confidence: float) -> str:
-    """Generate and publish BSV blockchain attestation."""
-    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S UTC")
-
-    # Create attestation data (no trade secrets - only results summary)
-    attestation_data = {
-        "platform": "TopoGrammar",
-        "version": "v2.1.0",
-        "timestamp": timestamp,
-        "analysis_type": "VUS_Resolution",
-        "variant_id": variant_id,
-        "classification": classification,
-        "confidence": round(confidence, 2),
-        "attestation_type": "demo"
-    }
-
-    # Create hash of the attestation data
-    data_str = json.dumps(attestation_data, sort_keys=True)
-    query_hash = hashlib.sha256(data_str.encode()).hexdigest()[:16]
-    full_hash = hashlib.sha256(data_str.encode()).hexdigest()
-
-    # Publish to BSV blockchain
-    txid = publish_to_bsv(attestation_data)
-
-    if txid:
-        # Real blockchain attestation
-        whatsonchain_url = f"https://whatsonchain.com/tx/{txid}"
-        status_line = f"Status: ✓ RECORDED ON BSV MAINNET"
-        txid_display = txid[:20] + "..." if len(txid) > 20 else txid
-        verify_section = f"""║  Transaction ID: {txid_display}
-║                                                              ║
-║  🔗 Verify on WhatsOnChain:                                  ║
-║  {whatsonchain_url[:54]}"""
-    else:
-        # Fallback if API fails
-        status_line = "Status: ⚠ OFFLINE MODE (BSV API unavailable)"
-        verify_section = f"""║  Data Hash:      {full_hash[:32]}...
-║                                                              ║
-║  ℹ Blockchain recording temporarily unavailable.             ║
-║  Result hash preserved for later attestation."""
-
-    return f"""
-```
-╔══════════════════════════════════════════════════════════════╗
-║           TOPOGRAMMAR BSV ATTESTATION CERTIFICATE            ║
-╠══════════════════════════════════════════════════════════════╣
-║                                                              ║
-║  Query Hash:     {query_hash}                    ║
-║  Timestamp:      {timestamp}                     ║
-║  Model Version:  TopoGrammar v2.1.0                         ║
-║                                                              ║
-║  ─────────────────────────────────────────────────────────  ║
-║                                                              ║
-║  Variant:        {variant_id}
-║  Classification: {classification}
-║  Confidence:     {confidence:.1%}
-║                                                              ║
-║  ─────────────────────────────────────────────────────────  ║
-║                                                              ║
-║  {status_line}
-║  Network: BSV Mainnet                                        ║
-║                                                              ║
-{verify_section}
-║                                                              ║
-║  This attestation is immutably recorded on BSV blockchain.  ║
-║  No proprietary algorithms or trade secrets are published.  ║
-║                                                              ║
-╚══════════════════════════════════════════════════════════════╝
-```
-"""
-
-
-def create_share_links(variant_id: str, classification: str) -> str:
-    """Create social sharing buttons."""
-    import urllib.parse
-
-    text = f"🧬 TopoGrammar reclassified {variant_id} as {classification}! Grammar-aware 3D genome analysis for precision medicine. #Genomics #AI #PrecisionMedicine"
-
-    twitter_url = f"https://twitter.com/intent/tweet?text={urllib.parse.quote(text)}&url=https://huggingface.co/spaces/GotThatData/TopoGrammar"
-    linkedin_url = f"https://www.linkedin.com/sharing/share-offsite/?url=https://huggingface.co/spaces/GotThatData/TopoGrammar"
-
-    return f"""
-<div style="display: flex; gap: 10px; margin-top: 20px;">
-    <a href="{twitter_url}" target="_blank" style="background: #1DA1F2; color: white; padding: 10px 20px; border-radius: 5px; text-decoration: none;">
-        🐦 Share on X
-    </a>
-    <a href="{linkedin_url}" target="_blank" style="background: #0077B5; color: white; padding: 10px 20px; border-radius: 5px; text-decoration: none;">
-        💼 Share on LinkedIn
-    </a>
-</div>
-"""
-
-
-# =============================================================================
-# Main Demo Functions
-# =============================================================================
-
-def run_vus_analysis(example_key: str) -> str:
-    """Run VUS resolution demo."""
-    if example_key not in VUS_EXAMPLES:
-        return "❌ Example not found. Please select a valid example."
-
-    # Simulate processing delay
-    time.sleep(1.5)
-
-    example = VUS_EXAMPLES[example_key]
-
-    # Build result markdown
-    result = f"""
-# 🧬 VUS Resolution Analysis
-
-## Variant Information
-| Field | Value |
-|-------|-------|
-| **Variant ID** | `{example['variant_id']}` |
-| **Gene** | {example['gene']} |
-| **Initial Classification** | {example['initial_class']} |
-
----
-
-## TopoGrammar Analysis Result
-
-### Classification Update
-| Before | → | After |
-|--------|---|-------|
-| **{example['initial_class']}** | 🔄 | **{example['final_class']}** |
-
-### Confidence Score
-{"█" * int(example['confidence'] * 20)}{"░" * (20 - int(example['confidence'] * 20))} **{example['confidence']:.0%}**
-
-### Primary Mechanism
-**{example['mechanism']}**
-
-### 3D Structural Impact
-- **Insulation Change**: {example['insulation_change']:+.0%}
-
----
-
-## Mechanism Visualization
-
-{create_grammar_diagram(example['mechanism'])}
-
----
-
-{create_confidence_bars(example['evidence_codes'], example['confidence'])}
-
----
-
-## Clinical Interpretation
-
-{example['description']}
-
----
-
-## BSV Verification
-
-{generate_bsv_attestation(example['variant_id'], example['final_class'], example['confidence'])}
-
----
-
-{create_share_links(example['variant_id'], example['final_class'])}
-"""
-
-    return result
-
-
-def run_tad_analysis(example_key: str) -> str:
-    """Run TAD detection demo."""
-    if example_key not in TAD_EXAMPLES:
-        return "❌ Example not found. Please select a valid example."
-
-    time.sleep(1.0)
-
-    example = TAD_EXAMPLES[example_key]
-
-    result = f"""
-# 🔬 TAD Detection Analysis
-
-## Region Information
-| Field | Value |
-|-------|-------|
-| **Region** | `{example['region']}` |
-| **TADs Detected** | {example['n_tads']} |
-| **Boundaries** | {example['n_boundaries']} |
-| **CTCF Sites** | {example['ctcf_sites']} |
-
----
-
-## Genes in Region
-{', '.join([f"**{g}**" for g in example['genes']])}
-
----
-
-## Contact Map Visualization
-
-```
-{create_contact_map_ascii(example['region'], example['n_tads'])}
-```
-
----
-
-## Boundary Strength Profile
-
-```
-{create_insulation_profile(example['boundary_strength'])}
-```
-
----
-
-## Detection Method
-
-TopoGrammar uses **CTCF-gated boundary detection** which achieves:
-- **91% TAD accuracy** (vs 80% for HiCCUPS)
-- **0.91 F1 score** for boundary detection
-- **Sub-TAD detection** capability
-
-The CTCF-gating mechanism ensures boundaries are only called where:
-1. Insulation score shows local minimum
-2. CTCF binding evidence is present
-3. Gradient analysis confirms boundary
-
----
-
-## Benchmark Comparison
-
-| Method | TAD Accuracy | Boundary F1 | Sub-TAD |
-|--------|-------------|-------------|---------|
-| **TopoGrammar** | **91%** | **0.91** | ✓ |
-| HiCCUPS | 80% | 0.76 | ✗ |
-| Arrowhead | 78% | 0.74 | ✗ |
-| TopDom | 75% | 0.71 | ✗ |
-"""
-
-    return result
-
-
-def run_neoloop_analysis(example_key: str) -> str:
-    """Run neo-loop detection demo."""
-    if example_key not in NEOLOOP_EXAMPLES:
-        return "❌ Example not found. Please select a valid example."
-
-    time.sleep(1.2)
-
-    example = NEOLOOP_EXAMPLES[example_key]
-
-    # Priority styling
-    if example['clinical_priority'] == "Critical":
-        priority_emoji = "🔴"
-        priority_style = "color: red; font-weight: bold;"
-    else:
-        priority_emoji = "🟡"
-        priority_style = "color: orange; font-weight: bold;"
-
-    result = f"""
-# 🧪 Neo-Loop Detection Analysis
-
-## Structural Variant
-| Field | Value |
-|-------|-------|
-| **SV Type** | `{example['sv_type']}` |
-| **Cancer Type** | {example['cancer_type']} |
-| **Clinical Priority** | {priority_emoji} **{example['clinical_priority']}** |
-
----
-
-## Oncogene Activation
-
-### Activated Oncogene
-**{example['oncogene']}**
-
-### Hijacked Enhancer
-**{example['hijacked_enhancer']}**
-
-### Neo-Loop Strength
-{"█" * int(example['loop_strength'] * 20)}{"░" * (20 - int(example['loop_strength'] * 20))} **{example['loop_strength']:.0%}**
-
----
-
-## Mechanism Visualization
-
-```
-┌─────────────────────────────────────────────────────────────┐
-│                    NEO-LOOP FORMATION                        │
-├─────────────────────────────────────────────────────────────┤
-│                                                             │
-│  BEFORE: {example['sv_type']}
-│  ┌────────────┐         ┌────────────┐                     │
-│  │  Enhancer  │─ ─ X ─ ─│  Oncogene  │                     │
-│  │  Domain A  │         │  Domain B  │                     │
-│  └────────────┘         └────────────┘                     │
-│       ↓                                                     │
-│   Normal Target                                             │
-│                                                             │
-│  AFTER: {example['sv_type']}
-│  ┌──────────────────────────────────────┐                  │
-│  │     Enhancer ══════════ Oncogene     │                  │
-│  │         ↓   NEO-LOOP   ↓             │                  │
-│  │      ABERRANT ACTIVATION             │                  │
-│  └──────────────────────────────────────┘                  │
-│                                                             │
-│  Loop Strength: {example['loop_strength']:.2f}
-│  Priority: {example['clinical_priority']}
-│                                                             │
-└─────────────────────────────────────────────────────────────┘
-```
-
----
-
-## Clinical Interpretation
-
-{example['description']}
-
----
-
-## Actionable Insights
-
-Based on this neo-loop detection:
-
-1. **Molecular Testing**: Confirm {example['sv_type']} by FISH or karyotyping
-2. **Targeted Therapy**: Consider therapies targeting {example['oncogene']} pathway
-3. **Clinical Trial**: Patient may be eligible for trials targeting this mechanism
-4. **Monitoring**: Track {example['oncogene']} expression as biomarker
-
----
-
-## BSV Verification
-
-{generate_bsv_attestation(example['sv_type'], f"Neo-loop: {example['oncogene']}", example['loop_strength'])}
-"""
-
-    return result
-
-
-def show_benchmarks() -> str:
-    """Show benchmark results."""
-    return f"""
-# 📊 TopoGrammar Benchmarks
-
-## TAD Detection Performance
-
-| Method | TAD Accuracy | Boundary F1 | Sub-TAD Detection |
-|--------|-------------|-------------|-------------------|
-| **TopoGrammar (CTCF-gated)** | **91%** | **0.91** | ✓ Yes |
-| HiCCUPS | 80% | 0.76 | ✗ No |
-| Arrowhead | 78% | 0.74 | ✗ No |
-| TopDom | 75% | 0.71 | ✗ No |
-
----
-
-## VUS Resolution Performance
-
-| Metric | Value |
-|--------|-------|
-| **Reclassification Rate** | 68% of VUS variants |
-| **Pathogenic Accuracy** | 93% |
-| **Mean Confidence Score** | 87% |
-
----
-
-## Insulation Density Improvement
-
-| Boundary Set | Insulation Ratio | P-value |
-|--------------|------------------|---------|
-| Major TADs only | 9.11x | <0.0001 |
-| **All Boundaries** | **15.57x** | **<0.0001** |
-| **Improvement** | **+70.9%** | — |
-
----
-
-## What Makes TopoGrammar Different
-
-### 1. Grammar-Aware Architecture
-
-Traditional tools see DNA as a string of letters. TopoGrammar sees it as **sentences with grammar**:
-
-```
-Reference:  [CTCF+] [Enhancer] [Promoter] [Gene]
-            "The enhancer activates the gene"
-
-Inversion:  [Gene] [Promoter] [Enhancer] [CTCF-]
-            "Gene the activates enhancer the"  ← SCRAMBLED
-```
-
-### 2. Physics + Semantics Concordance
-
-When both physics (insulation collapse) AND semantics (grammar scramble) agree:
-
-| Evidence Type | Alone | Concordant |
-|--------------|-------|------------|
-| Physics | PM1 (Moderate) | — |
-| Semantics | PM1 (Moderate) | — |
-| **Both** | — | **PS3 (Strong)** ← UPGRADE |
-
-### 3. CTCF-Gated Detection
-
-Unlike other tools, TopoGrammar only calls boundaries where:
-- ✓ Insulation score shows local minimum
-- ✓ CTCF binding evidence is present
-- ✓ Gradient analysis confirms boundary
-
-This reduces false positives by **40%** compared to insulation-only methods.
-
----
-
-## Clinical Value Pillars
-
-| Pillar | Clinical Value | Technical Foundation |
-|--------|---------------|---------------------|
-| **Architectural Fidelity** | Eliminates VUS by proving physical boundary collapse | PINN Physics (15.57x insulation) |
-| **Semantic Intelligence** | Detects "scrambled" instructions in balanced inversions | Regulatory Grammar Encoder |
-| **Privacy-First Growth** | Global model evolution without data leakage | Async Federated Learning |
-| **Clinician Clarity** | High-level medical prose instead of raw math | LLM Interpretation Layer |
-"""
-
-
-# =============================================================================
-# Gradio Interface
-# =============================================================================
-
-HEADER_MD = """
-# 🧬 TopoGrammar
-
-## The Industry's First Grammar-Aware 3D Genome Engine
-
-**Balanced Structural Variants (BSVs)** - inversions, translocations, complex rearrangements - appear "silent" to standard sequencers because they don't change gene dosage. But they **scramble the regulatory grammar** that controls gene expression.
-
-**TopoGrammar solves this.** It's the first engine that understands chromatin as a *language* with grammar rules that can be broken.
-
----
-
-| Capability | Performance |
-|------------|-------------|
-| 🎯 VUS Reclassification | 68% of variants |
-| 📊 Pathogenic Accuracy | 93% confidence |
-| 🔬 TAD Detection F1 | 0.91 (vs 0.76 HiCCUPS) |
-| ⚡ Sub-TAD Detection | Yes (unique capability) |
-
----
-"""
-
-ABOUT_MD = """
-# ℹ️ About TopoGrammar
-
-## Overview
-
-TopoGrammar is part of the **OmniPrime Enterprise Platform**, integrating:
-- **TopoGrammar v2.1.0** - Grammar-Aware 3D Genome Engine
-- **BioPrime v4.0 "Golden"** - Physics-First Molecular Docking
-
-Together, they enable a seamless **Patient Genome → Drug Candidate** workflow.
-
----
-
-## Core Innovation
-
-### Regulatory Grammar Analysis
-
-TopoGrammar treats regulatory elements as a **language**:
-
-```
-CTCF → Enhancer → Promoter → Gene
-   "The enhancer activates the gene"
-```
-
-When structural variants **scramble** this grammar, TopoGrammar detects it:
-
-```
-Gene ← Promoter ← Enhancer ← CTCF
-   "Gene the activates enhancer the"  ⚠ PATHOGENIC
-```
-
-### Semantic Break Score
-
-Quantifies regulatory disruption:
-- **Token Disruption (30%)**: Elements removed or duplicated
-- **Order Inversion (40%)**: Sequence rearranged
-- **Orientation Flip (30%)**: Strand direction reversed
-
----
-
-## Technology Stack
-
-- **Physics-Informed Neural Networks (PINNs)** for 3D reconstruction
-- **CTCF-Gated Boundary Detection** for precise TAD calling
-- **Federated Learning** for privacy-preserving multi-site training
-- **LLM Interpretation** for clinical reporting
-- **BSV Blockchain** for result attestation
-
----
-
-## Creators
-
-- **Bryan Daugherty**
-- **Gregory Ward**
-- **Shawn Ryan**
-
----
-
-## Learn More
-
-🌐 [bioprime.one](https://bioprime.one) | 🧬 [OmniPrime Platform](https://github.com/Saifullah62/OmniPrime_v1.0)
-
----
-
-**Copyright (c) 2026 Bryan Daugherty, Gregory Ward & Shawn Ryan. All Rights Reserved.**
-
-*This demo showcases TopoGrammar capabilities. Actual clinical use requires the full OmniPrime Enterprise Platform.*
-"""
-
-# Custom CSS
-CUSTOM_CSS = """
-.gradio-container {
-    background: linear-gradient(135deg, #1a1a2e 0%, #16213e 50%, #0f3460 100%);
-}
-.gr-button-primary {
-    background: linear-gradient(90deg, #00d4ff, #00ff88) !important;
-    border: none !important;
-}
-.gr-button-secondary {
-    background: linear-gradient(90deg, #667eea, #764ba2) !important;
-    border: none !important;
-    color: white !important;
-}
-"""
-
-# Build the interface
-with gr.Blocks(
-    title="TopoGrammar - Grammar-Aware 3D Genome Engine",
-    theme=gr.themes.Base(
-        primary_hue="cyan",
-        secondary_hue="purple",
-        neutral_hue="slate",
-    ),
-    css=CUSTOM_CSS,
-) as demo:
-
-    gr.Markdown(HEADER_MD)
-
-    with gr.Tabs():
-        # Tab 1: VUS Resolution
-        with gr.TabItem("🧬 VUS Resolution"):
-            gr.Markdown("""
-            ## Variant of Uncertain Significance → Clinical Classification
-
-            Select a demo variant to see how TopoGrammar reclassifies VUS using 3D genome analysis.
-            """)
-
-            with gr.Row():
-                with gr.Column(scale=1):
-                    gr.Markdown("### Select Example")
-                    vus_brca1 = gr.Button("🔴 BRCA1 Boundary Disruption", variant="secondary")
-                    vus_myc = gr.Button("🔴 MYC Enhancer Hijacking", variant="secondary")
-                    vus_shh = gr.Button("🟡 SHH Limb Enhancer", variant="secondary")
-                    vus_tp53 = gr.Button("🔴 TP53 Grammar Scrambling", variant="secondary")
-                    vus_benign = gr.Button("🟢 Benign Intronic SNP", variant="secondary")
-
-                with gr.Column(scale=3):
-                    vus_output = gr.Markdown("*Select an example to run VUS analysis*")
-
-            vus_brca1.click(fn=lambda: run_vus_analysis("brca1_boundary"), outputs=vus_output)
-            vus_myc.click(fn=lambda: run_vus_analysis("myc_enhancer_hijack"), outputs=vus_output)
-            vus_shh.click(fn=lambda: run_vus_analysis("sonic_hedgehog"), outputs=vus_output)
-            vus_tp53.click(fn=lambda: run_vus_analysis("tp53_scramble"), outputs=vus_output)
-            vus_benign.click(fn=lambda: run_vus_analysis("benign_intronic"), outputs=vus_output)
-
-        # Tab 2: TAD Detection
-        with gr.TabItem("🔬 TAD Detection"):
-            gr.Markdown("""
-            ## Topologically Associating Domain Detection
-
-            See how TopoGrammar detects TAD boundaries with CTCF-gating for 91% accuracy.
-            """)
-
-            with gr.Row():
-                with gr.Column(scale=1):
-                    gr.Markdown("### Select Region")
-                    tad_dscr = gr.Button("Chr21 - Down Syndrome Region", variant="secondary")
-                    tad_egfr = gr.Button("Chr7 - EGFR Locus", variant="secondary")
-                    tad_myc = gr.Button("Chr8 - MYC Oncogene", variant="secondary")
-
-                with gr.Column(scale=3):
-                    tad_output = gr.Markdown("*Select a region to analyze TAD structure*")
-
-            tad_dscr.click(fn=lambda: run_tad_analysis("chr21_dscr"), outputs=tad_output)
-            tad_egfr.click(fn=lambda: run_tad_analysis("chr7_egfr"), outputs=tad_output)
-            tad_myc.click(fn=lambda: run_tad_analysis("chr8_myc"), outputs=tad_output)
-
-        # Tab 3: Neo-Loop Detection
-        with gr.TabItem("🧪 Neo-Loop Detection"):
-            gr.Markdown("""
-            ## Cancer Neo-Loop & Enhancer Hijacking Detection
-
-            Identify oncogene activation through structural variant-induced neo-loops.
-            """)
-
-            with gr.Row():
-                with gr.Column(scale=1):
-                    gr.Markdown("### Select Cancer Example")
-                    neo_burkitt = gr.Button("🔴 Burkitt Lymphoma (MYC)", variant="secondary")
-                    neo_ewing = gr.Button("🔴 Ewing Sarcoma (EWSR1)", variant="secondary")
-                    neo_aml = gr.Button("🟡 AML (RUNX1)", variant="secondary")
-
-                with gr.Column(scale=3):
-                    neo_output = gr.Markdown("*Select a cancer example to detect neo-loops*")
-
-            neo_burkitt.click(fn=lambda: run_neoloop_analysis("burkitt_myc"), outputs=neo_output)
-            neo_ewing.click(fn=lambda: run_neoloop_analysis("ewing_ewsr1"), outputs=neo_output)
-            neo_aml.click(fn=lambda: run_neoloop_analysis("aml_runx1"), outputs=neo_output)
-
-        # Tab 4: Benchmarks
-        with gr.TabItem("📊 Benchmarks"):
-            gr.Markdown(show_benchmarks())
-
-        # Tab 5: About
-        with gr.TabItem("ℹ️ About"):
-            gr.Markdown(ABOUT_MD)
-
-    gr.Markdown("---")
-    gr.Markdown("""
-    <center>
-
-    **TopoGrammar v2.1.0** | Part of **OmniPrime Enterprise Platform**
-
-    [🌐 bioprime.one](https://bioprime.one) | [🧬 GitHub](https://github.com/Saifullah62/OmniPrime_v1.0) | [📧 Contact](mailto:info@bioprime.one)
-
-    *This is a demonstration. Clinical use requires the full OmniPrime Enterprise Platform.*
-
-    </center>
-    """)
-
-
-if __name__ == "__main__":
-    demo.launch()
+"""
+TopoGrammar - Grammar-Aware 3D Genome Engine Demo
+==================================================
+
+Hugging Face Spaces Demo for TopoGrammar v2.1.0
+The Industry's First Grammar-Aware Engine for Balanced Structural Variants
+
+Copyright (c) 2026 Bryan Daugherty, Gregory Ward & Shawn Ryan. All Rights Reserved.
+
+This demo showcases TopoGrammar's capabilities without exposing proprietary algorithms.
+All results are pre-computed demonstrations for educational purposes.
+"""
+
+import gradio as gr
+import hashlib
+import random
+import time
+import httpx
+import json
+import os
+from datetime import datetime
+from typing import Optional, Dict, List, Tuple
+
+# =============================================================================
+# BSV Blockchain Configuration
+# =============================================================================
+
+BSV_API_URL = "https://simplebsv.codenlighten.org"
+BSV_API_KEY = os.getenv("BSV_API_KEY")  # Set via HF Secrets
+
+
+def publish_to_bsv(data: Dict) -> Optional[str]:
+    """
+    Publish attestation data to BSV blockchain via SimpleBSV API.
+
+    Args:
+        data: Dictionary containing attestation data (no trade secrets)
+
+    Returns:
+        Transaction ID if successful, None otherwise
+    """
+    # Guard clause: fail gracefully if no key configured
+    if not BSV_API_KEY:
+        print("BSV_API_KEY not configured - running in offline mode")
+        return None
+    
+    try:
+        headers = {
+            "Content-Type": "application/json",
+            "x-api-key": BSV_API_KEY
+        }
+
+        # Use ?wait=true for synchronous response with txid
+        response = httpx.post(
+            f"{BSV_API_URL}/publish/json?wait=true",
+            headers=headers,
+            json={"json": data},
+            timeout=30.0
+        )
+
+        if response.status_code == 200:
+            result = response.json()
+            return result.get("txid")
+        else:
+            print(f"BSV API error: {response.status_code} - {response.text}")
+            return None
+
+    except Exception as e:
+        print(f"BSV publish error: {e}")
+        return None
+
+# =============================================================================
+# Demo Configuration - Pre-computed results (no trade secrets exposed)
+# =============================================================================
+
+# Demo VUS Examples with pre-computed classifications
+VUS_EXAMPLES = {
+    "brca1_boundary": {
+        "name": "BRCA1 TAD Boundary Disruption",
+        "variant_id": "chr17:43,044,295 G>A",
+        "gene": "BRCA1",
+        "initial_class": "VUS",
+        "final_class": "Pathogenic",
+        "confidence": 0.93,
+        "mechanism": "TAD Boundary Disruption",
+        "evidence_codes": ["PS3_insulation", "PM1_boundary", "PS3_ctcf"],
+        "insulation_change": -0.52,
+        "description": "This intronic variant disrupts a CTCF binding site at a critical TAD boundary, causing enhancer-promoter miscommunication affecting BRCA1 expression.",
+    },
+    "myc_enhancer_hijack": {
+        "name": "MYC Enhancer Hijacking",
+        "variant_id": "chr8:128,750,000 inv(500kb)",
+        "gene": "MYC",
+        "initial_class": "VUS",
+        "final_class": "Pathogenic",
+        "confidence": 0.89,
+        "mechanism": "Enhancer Hijacking",
+        "evidence_codes": ["PS3_neoloop", "PS2_oncogene", "PM1_boundary"],
+        "insulation_change": -0.68,
+        "description": "Balanced inversion creates a neo-loop connecting MYC to a hijacked super-enhancer, causing oncogene activation without copy number change.",
+    },
+    "sonic_hedgehog": {
+        "name": "SHH Limb Enhancer",
+        "variant_id": "chr7:156,584,000 del(50kb)",
+        "gene": "SHH",
+        "initial_class": "VUS",
+        "final_class": "Likely Pathogenic",
+        "confidence": 0.85,
+        "mechanism": "Enhancer Deletion",
+        "evidence_codes": ["PM1_regulatory", "PP3_conservation", "PS3_insulation"],
+        "insulation_change": -0.41,
+        "description": "Deletion removes the ZRS limb enhancer from SHH regulatory domain, disrupting developmental gene expression.",
+    },
+    "benign_intronic": {
+        "name": "Benign Intronic SNP",
+        "variant_id": "chr12:25,398,284 C>T",
+        "gene": "KRAS",
+        "initial_class": "VUS",
+        "final_class": "Benign",
+        "confidence": 0.91,
+        "mechanism": "No 3D Impact",
+        "evidence_codes": ["BS1_frequency", "BP4_no_disruption"],
+        "insulation_change": 0.02,
+        "description": "Deep intronic variant with no effect on TAD structure, CTCF binding, or regulatory grammar. Common in population databases.",
+    },
+    "tp53_scramble": {
+        "name": "TP53 Grammar Scrambling",
+        "variant_id": "chr17:7,670,000 inv(120kb)",
+        "gene": "TP53",
+        "initial_class": "VUS",
+        "final_class": "Pathogenic",
+        "confidence": 0.96,
+        "mechanism": "Regulatory Grammar Scrambling",
+        "evidence_codes": ["PS3_semantic", "PS3_insulation", "PM1_boundary", "PP3_conservation"],
+        "insulation_change": -0.71,
+        "description": "Balanced inversion scrambles the regulatory grammar of TP53, inverting enhancer-promoter orientation and disrupting tumor suppressor expression.",
+    },
+}
+
+# Demo TAD examples
+TAD_EXAMPLES = {
+    "chr21_dscr": {
+        "name": "Chromosome 21 - Down Syndrome Critical Region",
+        "region": "chr21:35,000,000-40,000,000",
+        "n_tads": 4,
+        "n_boundaries": 5,
+        "ctcf_sites": 12,
+        "genes": ["DSCR1", "DSCR3", "DSCR4", "RUNX1"],
+        "boundary_strength": [0.85, 0.92, 0.78, 0.88, 0.81],
+    },
+    "chr7_egfr": {
+        "name": "Chromosome 7 - EGFR Locus",
+        "region": "chr7:55,000,000-56,500,000",
+        "n_tads": 3,
+        "n_boundaries": 4,
+        "ctcf_sites": 8,
+        "genes": ["EGFR", "LANCL2", "VOPP1"],
+        "boundary_strength": [0.91, 0.87, 0.94, 0.82],
+    },
+    "chr8_myc": {
+        "name": "Chromosome 8 - MYC Oncogene",
+        "region": "chr8:127,500,000-129,500,000",
+        "n_tads": 2,
+        "n_boundaries": 3,
+        "ctcf_sites": 6,
+        "genes": ["MYC", "PVT1"],
+        "boundary_strength": [0.96, 0.89, 0.93],
+    },
+}
+
+# Demo Neo-Loop examples
+NEOLOOP_EXAMPLES = {
+    "burkitt_myc": {
+        "name": "Burkitt Lymphoma - MYC Translocation",
+        "sv_type": "Translocation t(8;14)",
+        "oncogene": "MYC",
+        "hijacked_enhancer": "IGH Super-Enhancer",
+        "loop_strength": 0.92,
+        "clinical_priority": "Critical",
+        "cancer_type": "Burkitt Lymphoma",
+        "description": "Classic t(8;14) translocation juxtaposes MYC with immunoglobulin heavy chain enhancers, creating pathogenic neo-loop.",
+    },
+    "ewing_ewsr1": {
+        "name": "Ewing Sarcoma - EWSR1-FLI1",
+        "sv_type": "Translocation t(11;22)",
+        "oncogene": "EWSR1-FLI1 fusion",
+        "hijacked_enhancer": "GGAA microsatellite enhancers",
+        "loop_strength": 0.88,
+        "clinical_priority": "Critical",
+        "cancer_type": "Ewing Sarcoma",
+        "description": "Fusion protein creates neo-loops at GGAA microsatellites, aberrantly activating developmental genes.",
+    },
+    "aml_runx1": {
+        "name": "AML - RUNX1 Disruption",
+        "sv_type": "Inversion inv(16)",
+        "oncogene": "CBFB-MYH11 fusion",
+        "hijacked_enhancer": "Myeloid enhancer cluster",
+        "loop_strength": 0.85,
+        "clinical_priority": "High",
+        "cancer_type": "Acute Myeloid Leukemia",
+        "description": "Pericentric inversion disrupts normal RUNX1 regulation, creating aberrant chromatin loops.",
+    },
+}
+
+# Benchmark comparisons
+BENCHMARK_DATA = {
+    "tad_detection": {
+        "TopoGrammar (CTCF-gated)": {"accuracy": 91, "f1": 0.91, "subtad": True},
+        "HiCCUPS": {"accuracy": 80, "f1": 0.76, "subtad": False},
+        "Arrowhead": {"accuracy": 78, "f1": 0.74, "subtad": False},
+        "TopDom": {"accuracy": 75, "f1": 0.71, "subtad": False},
+    },
+    "vus_resolution": {
+        "reclassification_rate": 68,
+        "pathogenic_accuracy": 93,
+        "mean_confidence": 87,
+    },
+    "insulation_density": {
+        "major_tads": 9.11,
+        "all_boundaries": 15.57,
+        "improvement": 70.9,
+    },
+}
+
+
+# =============================================================================
+# Visualization Functions
+# =============================================================================
+
+def create_contact_map_ascii(region: str, n_tads: int) -> str:
+    """Create ASCII representation of a Hi-C contact map with TADs."""
+    size = 40
+    map_lines = []
+
+    # Create diagonal pattern with TAD blocks
+    tad_size = size // n_tads
+
+    for i in range(size):
+        row = ""
+        for j in range(size):
+            if abs(i - j) <= 2:
+                row += "██"  # Diagonal
+            elif (i // tad_size) == (j // tad_size):
+                # Within same TAD
+                distance = abs(i - j)
+                if distance < tad_size // 2:
+                    row += "▓▓"
+                elif distance < tad_size:
+                    row += "░░"
+                else:
+                    row += "  "
+            else:
+                row += "  "
+        map_lines.append(row)
+
+    return "\n".join(map_lines)
+
+
+def create_insulation_profile(boundary_strengths: List[float]) -> str:
+    """Create ASCII insulation score profile."""
+    lines = []
+    lines.append("Insulation Score Profile:")
+    lines.append("=" * 60)
+
+    for i, strength in enumerate(boundary_strengths):
+        bar_len = int(strength * 40)
+        bar = "█" * bar_len + "░" * (40 - bar_len)
+        lines.append(f"Boundary {i+1}: [{bar}] {strength:.2f}")
+
+    lines.append("=" * 60)
+    return "\n".join(lines)
+
+
+def create_grammar_diagram(mechanism: str) -> str:
+    """Create regulatory grammar visualization."""
+    if mechanism == "Regulatory Grammar Scrambling":
+        return """
+┌─────────────────────────────────────────────────────────────┐
+│                  REGULATORY GRAMMAR ANALYSIS                 │
+├─────────────────────────────────────────────────────────────┤
+│                                                             │
+│  REFERENCE GRAMMAR:                                         │
+│  ┌──────┐   ┌──────────┐   ┌──────────┐   ┌──────┐        │
+│  │CTCF+ │ → │ ENHANCER │ → │ PROMOTER │ → │ GENE │        │
+│  └──────┘   └──────────┘   └──────────┘   └──────┘        │
+│  "The enhancer activates the gene"                         │
+│                                                             │
+│  VARIANT GRAMMAR (SCRAMBLED):                               │
+│  ┌──────┐   ┌──────────┐   ┌──────────┐   ┌──────┐        │
+│  │ GENE │ ← │ PROMOTER │ ← │ ENHANCER │ ← │CTCF- │        │
+│  └──────┘   └──────────┘   └──────────┘   └──────┘        │
+│  "Gene the activates enhancer the" ⚠ SCRAMBLED            │
+│                                                             │
+│  SEMANTIC BREAK SCORE: 0.85 (CRITICAL)                     │
+│  • Token Disruption: 30% weight                            │
+│  • Order Inversion: 40% weight                             │
+│  • Orientation Flip: 30% weight                            │
+│                                                             │
+└─────────────────────────────────────────────────────────────┘
+"""
+    elif mechanism == "Enhancer Hijacking":
+        return """
+┌─────────────────────────────────────────────────────────────┐
+│                   ENHANCER HIJACKING ANALYSIS                │
+├─────────────────────────────────────────────────────────────┤
+│                                                             │
+│  NORMAL TOPOLOGY:                                           │
+│  ┌─────────────────┐     ┌─────────────────┐               │
+│  │   TAD A         │     │   TAD B         │               │
+│  │ [Enhancer]──────│─X───│──────[Oncogene] │               │
+│  │      ↓          │     │                 │               │
+│  │  [Target Gene]  │     │                 │               ��
+│  └─────────────────┘     └─────────────────┘               │
+│         BOUNDARY BLOCKS CONTACT                             │
+│                                                             │
+│  AFTER STRUCTURAL VARIANT:                                  │
+│  ┌──────────────────────────────────────────┐              │
+│  │              FUSED TAD                    │              │
+│  │ [Enhancer]═══════════════════[Oncogene]  │              │
+│  │      ↓ NEO-LOOP FORMED ↓                 │              │
+│  │  [Target Gene]  ⚠ ONCOGENE ACTIVATED ⚠   │              │
+│  └──────────────────────────────────────────┘              │
+│                                                             │
+│  LOOP STRENGTH: 0.89 | PRIORITY: CRITICAL                  │
+│                                                             │
+└─────────────────────────────────────────────────────────────┘
+"""
+    elif mechanism == "TAD Boundary Disruption":
+        return """
+┌─────────────────────────────────────────────────────────────┐
+│                TAD BOUNDARY DISRUPTION ANALYSIS              │
+├─────────────────────────────────────────────────────────────┤
+│                                                             │
+│  NORMAL INSULATION:                                         │
+│  ████████████████ │ ████████████████                       │
+│      TAD A        │      TAD B                              │
+│                CTCF│CTCF                                    │
+│               ▲▲▲▲▲│▲▲▲▲▲                                   │
+│            Strong Boundary                                  │
+│                                                             │
+│  AFTER VARIANT (CTCF SITE DISRUPTED):                       │
+│  ████████████████   ████████████████                       │
+│      TAD A    ░░░░░░░   TAD B                              │
+│                 ↓↓↓↓↓                                       │
+│           Insulation Leak                                   │
+│                                                             │
+│  INSULATION CHANGE: -52%                                    │
+│  BOUNDARY LOSS: MAJOR                                       │
+│                                                             │
+└─────────────────────────────────────────────────────────────┘
+"""
+    else:
+        return """
+┌─────────────────────────────────────────────────────────────┐
+│                    3D GENOME ANALYSIS                        │
+├─────────────────────────────────────────────────────────────┤
+│                                                             │
+│  No significant 3D structural impact detected.              │
+│                                                             │
+│  • TAD boundaries: INTACT                                   │
+│  • Insulation scores: NORMAL                                │
+│  • Regulatory grammar: PRESERVED                            │
+│  • CTCF binding: UNAFFECTED                                 │
+│                                                             │
+└─────────────────────────────────────────────────────────────┘
+"""
+
+
+def create_confidence_bars(evidence_codes: List[str], confidence: float) -> str:
+    """Create evidence code visualization."""
+    lines = []
+    lines.append("\n### Evidence Summary\n")
+
+    for code in evidence_codes:
+        # Determine strength from code prefix
+        if code.startswith("PS"):
+            strength = "Strong"
+            bar = "████████████████████"
+            color = "🟢"
+        elif code.startswith("PM"):
+            strength = "Moderate"
+            bar = "████████████░░░░░░░░"
+            color = "🟡"
+        elif code.startswith("PP"):
+            strength = "Supporting"
+            bar = "████████░░░░░░░░░░░░"
+            color = "🟠"
+        elif code.startswith("BS") or code.startswith("BP"):
+            strength = "Benign"
+            bar = "████████████████████"
+            color = "🔵"
+        else:
+            strength = "Unknown"
+            bar = "░░░░░░░░░░░░░░░░░░░░"
+            color = "⚪"
+
+        lines.append(f"{color} **{code}** ({strength}): `{bar}`")
+
+    lines.append(f"\n**Overall Confidence**: {confidence:.0%}")
+
+    return "\n".join(lines)
+
+
+def generate_bsv_attestation(variant_id: str, classification: str, confidence: float) -> str:
+    """Generate and publish BSV blockchain attestation."""
+    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S UTC")
+
+    # Create attestation data (no trade secrets - only results summary)
+    attestation_data = {
+        "platform": "TopoGrammar",
+        "version": "v2.1.0",
+        "timestamp": timestamp,
+        "analysis_type": "VUS_Resolution",
+        "variant_id": variant_id,
+        "classification": classification,
+        "confidence": round(confidence, 2),
+        "attestation_type": "demo"
+    }
+
+    # Create hash of the attestation data
+    data_str = json.dumps(attestation_data, sort_keys=True)
+    query_hash = hashlib.sha256(data_str.encode()).hexdigest()[:16]
+    full_hash = hashlib.sha256(data_str.encode()).hexdigest()
+
+    # Publish to BSV blockchain
+    txid = publish_to_bsv(attestation_data)
+
+    if txid:
+        # Real blockchain attestation
+        whatsonchain_url = f"https://whatsonchain.com/tx/{txid}"
+        status_line = f"Status: ✓ RECORDED ON BSV MAINNET"
+        txid_display = txid[:20] + "..." if len(txid) > 20 else txid
+        verify_section = f"""║  Transaction ID: {txid_display}
+║                                                              ║
+║  🔗 Verify on WhatsOnChain:                                  ║
+║  {whatsonchain_url[:54]}"""
+    else:
+        # Fallback if API fails
+        status_line = "Status: ⚠ OFFLINE MODE (BSV API unavailable)"
+        verify_section = f"""║  Data Hash:      {full_hash[:32]}...
+║                                                              ║
+║  ℹ Blockchain recording temporarily unavailable.             ║
+║  Result hash preserved for later attestation."""
+
+    return f"""
+```
+╔══════════════════════════════════════════════════════════════╗
+║           TOPOGRAMMAR BSV ATTESTATION CERTIFICATE            ║
+╠══════════════════════════════════════════════════════════════╣
+║                                                              ║
+║  Query Hash:     {query_hash}                    ║
+║  Timestamp:      {timestamp}                     ║
+║  Model Version:  TopoGrammar v2.1.0                         ║
+║                                                              ║
+║  ─────────────────────────────────────────────────────────  ║
+║                                                              ║
+║  Variant:        {variant_id}
+║  Classification: {classification}
+║  Confidence:     {confidence:.1%}
+║                                                              ║
+║  ─────────────────────────────────────────────────────────  ║
+║                                                              ║
+║  {status_line}
+║  Network: BSV Mainnet                                        ║
+║                                                              ║
+{verify_section}
+║                                                              ║
+║  This attestation is immutably recorded on BSV blockchain.  ║
+║  No proprietary algorithms or trade secrets are published.  ║
+║                                                              ║
+╚══════════════════════════════════════════════════════════════╝
+```
+"""
+
+
+def create_share_links(variant_id: str, classification: str) -> str:
+    """Create social sharing buttons."""
+    import urllib.parse
+
+    text = f"🧬 TopoGrammar reclassified {variant_id} as {classification}! Grammar-aware 3D genome analysis for precision medicine. #Genomics #AI #PrecisionMedicine"
+
+    twitter_url = f"https://twitter.com/intent/tweet?text={urllib.parse.quote(text)}&url=https://huggingface.co/spaces/GotThatData/TopoGrammar"
+    linkedin_url = f"https://www.linkedin.com/sharing/share-offsite/?url=https://huggingface.co/spaces/GotThatData/TopoGrammar"
+
+    return f"""
+<div style="display: flex; gap: 10px; margin-top: 20px;">
+    <a href="{twitter_url}" target="_blank" style="background: #1DA1F2; color: white; padding: 10px 20px; border-radius: 5px; text-decoration: none;">
+        🐦 Share on X
+    </a>
+    <a href="{linkedin_url}" target="_blank" style="background: #0077B5; color: white; padding: 10px 20px; border-radius: 5px; text-decoration: none;">
+        💼 Share on LinkedIn
+    </a>
+</div>
+"""
+
+
+# =============================================================================
+# Main Demo Functions
+# =============================================================================
+
+def run_vus_analysis(example_key: str) -> str:
+    """Run VUS resolution demo."""
+    if example_key not in VUS_EXAMPLES:
+        return "❌ Example not found. Please select a valid example."
+
+    # Simulate processing delay
+    time.sleep(1.5)
+
+    example = VUS_EXAMPLES[example_key]
+
+    # Build result markdown
+    result = f"""
+# 🧬 VUS Resolution Analysis
+
+## Variant Information
+| Field | Value |
+|-------|-------|
+| **Variant ID** | `{example['variant_id']}` |
+| **Gene** | {example['gene']} |
+| **Initial Classification** | {example['initial_class']} |
+
+---
+
+## TopoGrammar Analysis Result
+
+### Classification Update
+| Before | → | After |
+|--------|---|-------|
+| **{example['initial_class']}** | 🔄 | **{example['final_class']}** |
+
+### Confidence Score
+{"█" * int(example['confidence'] * 20)}{"░" * (20 - int(example['confidence'] * 20))} **{example['confidence']:.0%}**
+
+### Primary Mechanism
+**{example['mechanism']}**
+
+### 3D Structural Impact
+- **Insulation Change**: {example['insulation_change']:+.0%}
+
+---
+
+## Mechanism Visualization
+
+{create_grammar_diagram(example['mechanism'])}
+
+---
+
+{create_confidence_bars(example['evidence_codes'], example['confidence'])}
+
+---
+
+## Clinical Interpretation
+
+{example['description']}
+
+---
+
+## BSV Verification
+
+{generate_bsv_attestation(example['variant_id'], example['final_class'], example['confidence'])}
+
+---
+
+{create_share_links(example['variant_id'], example['final_class'])}
+"""
+
+    return result
+
+
+def run_tad_analysis(example_key: str) -> str:
+    """Run TAD detection demo."""
+    if example_key not in TAD_EXAMPLES:
+        return "❌ Example not found. Please select a valid example."
+
+    time.sleep(1.0)
+
+    example = TAD_EXAMPLES[example_key]
+
+    result = f"""
+# 🔬 TAD Detection Analysis
+
+## Region Information
+| Field | Value |
+|-------|-------|
+| **Region** | `{example['region']}` |
+| **TADs Detected** | {example['n_tads']} |
+| **Boundaries** | {example['n_boundaries']} |
+| **CTCF Sites** | {example['ctcf_sites']} |
+
+---
+
+## Genes in Region
+{', '.join([f"**{g}**" for g in example['genes']])}
+
+---
+
+## Contact Map Visualization
+
+```
+{create_contact_map_ascii(example['region'], example['n_tads'])}
+```
+
+---
+
+## Boundary Strength Profile
+
+```
+{create_insulation_profile(example['boundary_strength'])}
+```
+
+---
+
+## Detection Method
+
+TopoGrammar uses **CTCF-gated boundary detection** which achieves:
+- **91% TAD accuracy** (vs 80% for HiCCUPS)
+- **0.91 F1 score** for boundary detection
+- **Sub-TAD detection** capability
+
+The CTCF-gating mechanism ensures boundaries are only called where:
+1. Insulation score shows local minimum
+2. CTCF binding evidence is present
+3. Gradient analysis confirms boundary
+
+---
+
+## Benchmark Comparison
+
+| Method | TAD Accuracy | Boundary F1 | Sub-TAD |
+|--------|-------------|-------------|---------|
+| **TopoGrammar** | **91%** | **0.91** | ✓ |
+| HiCCUPS | 80% | 0.76 | ✗ |
+| Arrowhead | 78% | 0.74 | ✗ |
+| TopDom | 75% | 0.71 | ✗ |
+"""
+
+    return result
+
+
+def run_neoloop_analysis(example_key: str) -> str:
+    """Run neo-loop detection demo."""
+    if example_key not in NEOLOOP_EXAMPLES:
+        return "❌ Example not found. Please select a valid example."
+
+    time.sleep(1.2)
+
+    example = NEOLOOP_EXAMPLES[example_key]
+
+    # Priority styling
+    if example['clinical_priority'] == "Critical":
+        priority_emoji = "🔴"
+        priority_style = "color: red; font-weight: bold;"
+    else:
+        priority_emoji = "🟡"
+        priority_style = "color: orange; font-weight: bold;"
+
+    result = f"""
+# ��� Neo-Loop Detection Analysis
+
+## Structural Variant
+| Field | Value |
+|-------|-------|
+| **SV Type** | `{example['sv_type']}` |
+| **Cancer Type** | {example['cancer_type']} |
+| **Clinical Priority** | {priority_emoji} **{example['clinical_priority']}** |
+
+---
+
+## Oncogene Activation
+
+### Activated Oncogene
+**{example['oncogene']}**
+
+### Hijacked Enhancer
+**{example['hijacked_enhancer']}**
+
+### Neo-Loop Strength
+{"█" * int(example['loop_strength'] * 20)}{"░" * (20 - int(example['loop_strength'] * 20))} **{example['loop_strength']:.0%}**
+
+---
+
+## Mechanism Visualization
+
+```
+┌─────────────────────────────────────────────────────────────┐
+│                    NEO-LOOP FORMATION                        │
+├─────────────────────────────────────────────────────────────┤
+│                                                             │
+│  BEFORE: {example['sv_type']}
+│  ┌────────────┐         ┌────────────┐                     │
+│  │  Enhancer  │─ ─ X ─ ─│  Oncogene  │                     │
+│  │  Domain A  │         │  Domain B  │                     │
+│  └────────────┘         └────────────┘                     │
+│       ↓                                                     │
+│   Normal Target                                             │
+│                                                             │
+│  AFTER: {example['sv_type']}
+│  ┌──────────────────────────────────────┐                  │
+│  │     Enhancer ══════════ Oncogene     │                  │
+│  │         ↓   NEO-LOOP   ↓             │                  │
+│  │      ABERRANT ACTIVATION             │                  │
+│  └──────────────────────────────────────┘                  │
+│                                                             │
+│  Loop Strength: {example['loop_strength']:.2f}
+│  Priority: {example['clinical_priority']}
+│                                                             │
+└─────────────────────────────────────────────────────────────┘
+```
+
+---
+
+## Clinical Interpretation
+
+{example['description']}
+
+---
+
+## Actionable Insights
+
+Based on this neo-loop detection:
+
+1. **Molecular Testing**: Confirm {example['sv_type']} by FISH or karyotyping
+2. **Targeted Therapy**: Consider therapies targeting {example['oncogene']} pathway
+3. **Clinical Trial**: Patient may be eligible for trials targeting this mechanism
+4. **Monitoring**: Track {example['oncogene']} expression as biomarker
+
+---
+
+## BSV Verification
+
+{generate_bsv_attestation(example['sv_type'], f"Neo-loop: {example['oncogene']}", example['loop_strength'])}
+"""
+
+    return result
+
+
+def show_benchmarks() -> str:
+    """Show benchmark results."""
+    return f"""
+# 📊 TopoGrammar Benchmarks
+
+## TAD Detection Performance
+
+| Method | TAD Accuracy | Boundary F1 | Sub-TAD Detection |
+|--------|-------------|-------------|-------------------|
+| **TopoGrammar (CTCF-gated)** | **91%** | **0.91** | ✓ Yes |
+| HiCCUPS | 80% | 0.76 | ✗ No |
+| Arrowhead | 78% | 0.74 | ✗ No |
+| TopDom | 75% | 0.71 | ✗ No |
+
+---
+
+## VUS Resolution Performance
+
+| Metric | Value |
+|--------|-------|
+| **Reclassification Rate** | 68% of VUS variants |
+| **Pathogenic Accuracy** | 93% |
+| **Mean Confidence Score** | 87% |
+
+---
+
+## Insulation Density Improvement
+
+| Boundary Set | Insulation Ratio | P-value |
+|--------------|------------------|---------|
+| Major TADs only | 9.11x | <0.0001 |
+| **All Boundaries** | **15.57x** | **<0.0001** |
+| **Improvement** | **+70.9%** | — |
+
+---
+
+## What Makes TopoGrammar Different
+
+### 1. Grammar-Aware Architecture
+
+Traditional tools see DNA as a string of letters. TopoGrammar sees it as **sentences with grammar**:
+
+```
+Reference:  [CTCF+] [Enhancer] [Promoter] [Gene]
+            "The enhancer activates the gene"
+
+Inversion:  [Gene] [Promoter] [Enhancer] [CTCF-]
+            "Gene the activates enhancer the"  ← SCRAMBLED
+```
+
+### 2. Physics + Semantics Concordance
+
+When both physics (insulation collapse) AND semantics (grammar scramble) agree:
+
+| Evidence Type | Alone | Concordant |
+|--------------|-------|------------|
+| Physics | PM1 (Moderate) | — |
+| Semantics | PM1 (Moderate) | — |
+| **Both** | — | **PS3 (Strong)** ← UPGRADE |
+
+### 3. CTCF-Gated Detection
+
+Unlike other tools, TopoGrammar only calls boundaries where:
+- ✓ Insulation score shows local minimum
+- ✓ CTCF binding evidence is present
+- ✓ Gradient analysis confirms boundary
+
+This reduces false positives by **40%** compared to insulation-only methods.
+
+---
+
+## Clinical Value Pillars
+
+| Pillar | Clinical Value | Technical Foundation |
+|--------|---------------|---------------------|
+| **Architectural Fidelity** | Eliminates VUS by proving physical boundary collapse | PINN Physics (15.57x insulation) |
+| **Semantic Intelligence** | Detects "scrambled" instructions in balanced inversions | Regulatory Grammar Encoder |
+| **Privacy-First Growth** | Global model evolution without data leakage | Async Federated Learning |
+| **Clinician Clarity** | High-level medical prose instead of raw math | LLM Interpretation Layer |
+"""
+
+
+# =============================================================================
+# Gradio Interface
+# =============================================================================
+
+HEADER_MD = """
+# 🧬 TopoGrammar
+
+## The Industry's First Grammar-Aware 3D Genome Engine
+
+**Balanced Structural Variants (BSVs)** - inversions, translocations, complex rearrangements - appear "silent" to standard sequencers because they don't change gene dosage. But they **scramble the regulatory grammar** that controls gene expression.
+
+**TopoGrammar solves this.** It's the first engine that understands chromatin as a *language* with grammar rules that can be broken.
+
+---
+
+| Capability | Performance |
+|------------|-------------|
+| 🎯 VUS Reclassification | 68% of variants |
+| 📊 Pathogenic Accuracy | 93% confidence |
+| 🔬 TAD Detection F1 | 0.91 (vs 0.76 HiCCUPS) |
+| ⚡ Sub-TAD Detection | Yes (unique capability) |
+
+---
+"""
+
+ABOUT_MD = """
+# ℹ️ About TopoGrammar
+
+## Overview
+
+TopoGrammar is part of the **OmniPrime Enterprise Platform**, integrating:
+- **TopoGrammar v2.1.0** - Grammar-Aware 3D Genome Engine
+- **BioPrime v4.0 "Golden"** - Physics-First Molecular Docking
+
+Together, they enable a seamless **Patient Genome → Drug Candidate** workflow.
+
+---
+
+## Core Innovation
+
+### Regulatory Grammar Analysis
+
+TopoGrammar treats regulatory elements as a **language**:
+
+```
+CTCF → Enhancer → Promoter → Gene
+   "The enhancer activates the gene"
+```
+
+When structural variants **scramble** this grammar, TopoGrammar detects it:
+
+```
+Gene ← Promoter ← Enhancer ← CTCF
+   "Gene the activates enhancer the"  ⚠ PATHOGENIC
+```
+
+### Semantic Break Score
+
+Quantifies regulatory disruption:
+- **Token Disruption (30%)**: Elements removed or duplicated
+- **Order Inversion (40%)**: Sequence rearranged
+- **Orientation Flip (30%)**: Strand direction reversed
+
+---
+
+## Technology Stack
+
+- **Physics-Informed Neural Networks (PINNs)** for 3D reconstruction
+- **CTCF-Gated Boundary Detection** for precise TAD calling
+- **Federated Learning** for privacy-preserving multi-site training
+- **LLM Interpretation** for clinical reporting
+- **BSV Blockchain** for result attestation
+
+---
+
+## Creators
+
+- **Bryan Daugherty**
+- **Gregory Ward**
+- **Shawn Ryan**
+
+---
+
+## Learn More
+
+🌐 [bioprime.one](https://bioprime.one) | 🧬 [OmniPrime Platform](https://github.com/Saifullah62/OmniPrime_v1.0)
+
+---
+
+**Copyright (c) 2026 Bryan Daugherty, Gregory Ward & Shawn Ryan. All Rights Reserved.**
+
+*This demo showcases TopoGrammar capabilities. Actual clinical use requires the full OmniPrime Enterprise Platform.*
+"""
+
+# Custom CSS
+CUSTOM_CSS = """
+.gradio-container {
+    background: linear-gradient(135deg, #1a1a2e 0%, #16213e 50%, #0f3460 100%);
+}
+.gr-button-primary {
+    background: linear-gradient(90deg, #00d4ff, #00ff88) !important;
+    border: none !important;
+}
+.gr-button-secondary {
+    background: linear-gradient(90deg, #667eea, #764ba2) !important;
+    border: none !important;
+    color: white !important;
+}
+"""
+
+# Build the interface
+with gr.Blocks(
+    title="TopoGrammar - Grammar-Aware 3D Genome Engine",
+    theme=gr.themes.Base(
+        primary_hue="cyan",
+        secondary_hue="purple",
+        neutral_hue="slate",
+    ),
+    css=CUSTOM_CSS,
+) as demo:
+
+    gr.Markdown(HEADER_MD)
+
+    with gr.Tabs():
+        # Tab 1: VUS Resolution
+        with gr.TabItem("🧬 VUS Resolution"):
+            gr.Markdown("""
+            ## Variant of Uncertain Significance → Clinical Classification
+
+            Select a demo variant to see how TopoGrammar reclassifies VUS using 3D genome analysis.
+            """)
+
+            with gr.Row():
+                with gr.Column(scale=1):
+                    gr.Markdown("### Select Example")
+                    vus_brca1 = gr.Button("🔴 BRCA1 Boundary Disruption", variant="secondary")
+                    vus_myc = gr.Button("🔴 MYC Enhancer Hijacking", variant="secondary")
+                    vus_shh = gr.Button("🟡 SHH Limb Enhancer", variant="secondary")
+                    vus_tp53 = gr.Button("🔴 TP53 Grammar Scrambling", variant="secondary")
+                    vus_benign = gr.Button("🟢 Benign Intronic SNP", variant="secondary")
+
+                with gr.Column(scale=3):
+                    vus_output = gr.Markdown("*Select an example to run VUS analysis*")
+
+            vus_brca1.click(fn=lambda: run_vus_analysis("brca1_boundary"), outputs=vus_output)
+            vus_myc.click(fn=lambda: run_vus_analysis("myc_enhancer_hijack"), outputs=vus_output)
+            vus_shh.click(fn=lambda: run_vus_analysis("sonic_hedgehog"), outputs=vus_output)
+            vus_tp53.click(fn=lambda: run_vus_analysis("tp53_scramble"), outputs=vus_output)
+            vus_benign.click(fn=lambda: run_vus_analysis("benign_intronic"), outputs=vus_output)
+
+        # Tab 2: TAD Detection
+        with gr.TabItem("🔬 TAD Detection"):
+            gr.Markdown("""
+            ## Topologically Associating Domain Detection
+
+            See how TopoGrammar detects TAD boundaries with CTCF-gating for 91% accuracy.
+            """)
+
+            with gr.Row():
+                with gr.Column(scale=1):
+                    gr.Markdown("### Select Region")
+                    tad_dscr = gr.Button("Chr21 - Down Syndrome Region", variant="secondary")
+                    tad_egfr = gr.Button("Chr7 - EGFR Locus", variant="secondary")
+                    tad_myc = gr.Button("Chr8 - MYC Oncogene", variant="secondary")
+
+                with gr.Column(scale=3):
+                    tad_output = gr.Markdown("*Select a region to analyze TAD structure*")
+
+            tad_dscr.click(fn=lambda: run_tad_analysis("chr21_dscr"), outputs=tad_output)
+            tad_egfr.click(fn=lambda: run_tad_analysis("chr7_egfr"), outputs=tad_output)
+            tad_myc.click(fn=lambda: run_tad_analysis("chr8_myc"), outputs=tad_output)
+
+        # Tab 3: Neo-Loop Detection
+        with gr.TabItem("🧪 Neo-Loop Detection"):
+            gr.Markdown("""
+            ## Cancer Neo-Loop & Enhancer Hijacking Detection
+
+            Identify oncogene activation through structural variant-induced neo-loops.
+            """)
+
+            with gr.Row():
+                with gr.Column(scale=1):
+                    gr.Markdown("### Select Cancer Example")
+                    neo_burkitt = gr.Button("🔴 Burkitt Lymphoma (MYC)", variant="secondary")
+                    neo_ewing = gr.Button("🔴 Ewing Sarcoma (EWSR1)", variant="secondary")
+                    neo_aml = gr.Button("🟡 AML (RUNX1)", variant="secondary")
+
+                with gr.Column(scale=3):
+                    neo_output = gr.Markdown("*Select a cancer example to detect neo-loops*")
+
+            neo_burkitt.click(fn=lambda: run_neoloop_analysis("burkitt_myc"), outputs=neo_output)
+            neo_ewing.click(fn=lambda: run_neoloop_analysis("ewing_ewsr1"), outputs=neo_output)
+            neo_aml.click(fn=lambda: run_neoloop_analysis("aml_runx1"), outputs=neo_output)
+
+        # Tab 4: Benchmarks
+        with gr.TabItem("📊 Benchmarks"):
+            gr.Markdown(show_benchmarks())
+
+        # Tab 5: About
+        with gr.TabItem("ℹ️ About"):
+            gr.Markdown(ABOUT_MD)
+
+    gr.Markdown("---")
+    gr.Markdown("""
+    <center>
+
+    **TopoGrammar v2.1.0** | Part of **OmniPrime Enterprise Platform**
+
+    [🌐 bioprime.one](https://bioprime.one) | [🧬 GitHub](https://github.com/Saifullah62/OmniPrime_v1.0) | [📧 Contact](mailto:info@bioprime.one)
+
+    *This is a demonstration. Clinical use requires the full OmniPrime Enterprise Platform.*
+
+    </center>
+    """)
+
+
+if __name__ == "__main__":
+    demo.launch()