diff --git a/BIOHACKING - DNA NODE INTERGATION SYSTEM b/BIOHACKING - DNA NODE INTERGATION SYSTEM new file mode 100644 index 0000000..b9e989c --- /dev/null +++ b/BIOHACKING - DNA NODE INTERGATION SYSTEM @@ -0,0 +1,739 @@ +#!/usr/bin/env python3 +""" +BIOHACKING - DNA/RNA NODE INTEGRATION SYSTEM +=============================================== +Complete biological interface for neural nodes with: +- DNA data storage and retrieval +- RNA/mRNA/tRNA signal translation +- Genetic sequence to RF frequency mapping +- Epigenetic modulation via node stimulation +- CRISPR-based node programming + +This system bridges biological genetics with RF neural nodes, +enabling DNA/RNA to control node behavior and vice versa. +""" + +import numpy as np +import hashlib +import json +import time +import zlib +from typing import Dict, List, Tuple, Optional +from dataclasses import dataclass, field +from enum import Enum + +# ============================================================================= +# SECTION 1: DNA/RNA SEQUENCE TO RF FREQUENCY MAPPING +# ============================================================================= + +class GeneticToRFMapper: + """ + Maps DNA/RNA sequences to RF frequencies for node communication + Each genetic sequence has a unique RF signature + """ + + # Nucleotide to base frequency mapping (GHz) + NUCLEOTIDE_FREQS = { + 'A': 10.23, # Adenine + 'T': 10.24, # Thymine (DNA) + 'U': 10.25, # Uracil (RNA) + 'G': 10.26, # Guanine + 'C': 10.27, # Cytosine + } + + # Codon to frequency offset (MHz) + CODON_OFFSETS = { + 'AUG': 0.000, # Start codon (Methionine) + 'UAA': 0.050, # Stop codon + 'UAG': 0.051, # Stop codon + 'UGA': 0.052, # Stop codon + # Common amino acids + 'UUU': 0.010, 'UUC': 0.011, # Phenylalanine + 'UUA': 0.012, 'UUG': 0.013, # Leucine + 'CUU': 0.014, 'CUC': 0.015, # Leucine + 'AUU': 0.016, 'AUC': 0.017, # Isoleucine + 'AUA': 0.018, 'AUG': 0.019, # Methionine + 'GUU': 0.020, 'GUC': 0.021, # Valine + 'UCU': 0.022, 'UCC': 0.023, # Serine + 'CCU': 0.024, 'CCC': 0.025, # Proline + 'ACU': 0.026, 'ACC': 0.027, # Threonine + 'GCU': 0.028, 'GCC': 0.029, # Alanine + 'UAU': 0.030, 'UAC': 0.031, # Tyrosine + 'CAU': 0.032, 'CAC': 0.033, # Histidine + 'CAA': 0.034, 'CAG': 0.035, # Glutamine + 'AAU': 0.036, 'AAC': 0.037, # Asparagine + 'AAA': 0.038, 'AAG': 0.039, # Lysine + 'GAU': 0.040, 'GAC': 0.041, # Aspartic acid + 'GAA': 0.042, 'GAG': 0.043, # Glutamic acid + 'UGU': 0.044, 'UGC': 0.045, # Cysteine + 'UGG': 0.046, # Tryptophan + 'CGU': 0.047, 'CGC': 0.048, # Arginine + 'AGU': 0.049, 'AGC': 0.050, # Serine + 'AGA': 0.051, 'AGG': 0.052, # Arginine + 'GGU': 0.053, 'GGC': 0.054, # Glycine + } + + @classmethod + def dna_to_frequency(cls, dna_sequence: str) -> Dict: + """ + Convert DNA sequence to RF frequency signature + Each DNA sequence produces a unique frequency pattern + """ + # Base frequency from nucleotide average + freqs = [cls.NUCLEOTIDE_FREQS.get(c, 10.25) for c in dna_sequence.upper()] + base_freq = np.mean(freqs) + + # Codon modulation + codons = [dna_sequence[i:i+3] for i in range(0, len(dna_sequence), 3)] + codon_mod = sum(cls.CODON_OFFSETS.get(codon, 0.025) for codon in codons) / max(1, len(codons)) + + final_freq = base_freq + codon_mod + + # Create frequency fingerprint + fingerprint = hashlib.sha3_256(dna_sequence.encode()).hexdigest()[:16] + + return { + 'dna_sequence': dna_sequence, + 'base_frequency_ghz': round(base_freq, 4), + 'codon_modulation_ghz': round(codon_mod, 4), + 'resonance_frequency_ghz': round(final_freq, 4), + 'fingerprint': fingerprint, + 'node_tuning_parameter': final_freq - 10.23 + } + + @classmethod + def rna_to_frequency(cls, rna_sequence: str) -> Dict: + """Convert RNA sequence (U instead of T) to RF frequency""" + # RNA uses Uracil instead of Thymine + dna_equivalent = rna_sequence.replace('U', 'T') + return cls.dna_to_frequency(dna_equivalent) + + @classmethod + def mrna_to_frequency(cls, mrna_sequence: str) -> Dict: + """mRNA (messenger RNA) to frequency - used for protein coding""" + result = cls.rna_to_frequency(mrna_sequence) + result['type'] = 'mRNA' + result['protein_encoded'] = cls.translate_mrna_to_protein(mrna_sequence) + return result + + @classmethod + def trna_to_frequency(cls, trna_anticodon: str) -> Dict: + """tRNA anticodon to frequency - used for amino acid delivery""" + # tRNA anticodon is 3 bases + anticodon = trna_anticodon.upper()[:3] + result = cls.rna_to_frequency(anticodon) + result['type'] = 'tRNA' + result['anticodon'] = anticodon + result['carries_amino_acid'] = cls.codon_to_amino_acid(anticodon) + return result + + @classmethod + def translate_mrna_to_protein(cls, mrna: str) -> List[str]: + """Translate mRNA to amino acid sequence""" + amino_acids = [] + for i in range(0, len(mrna), 3): + codon = mrna[i:i+3] + if len(codon) == 3: + aa = cls.codon_to_amino_acid(codon) + if aa: + amino_acids.append(aa) + return amino_acids + + @classmethod + def codon_to_amino_acid(cls, codon: str) -> str: + """Convert codon to amino acid (3-letter code)""" + codon_table = { + 'UUU': 'Phe', 'UUC': 'Phe', 'UUA': 'Leu', 'UUG': 'Leu', + 'CUU': 'Leu', 'CUC': 'Leu', 'CUA': 'Leu', 'CUG': 'Leu', + 'AUU': 'Ile', 'AUC': 'Ile', 'AUA': 'Ile', 'AUG': 'Met', + 'GUU': 'Val', 'GUC': 'Val', 'GUA': 'Val', 'GUG': 'Val', + 'UCU': 'Ser', 'UCC': 'Ser', 'UCA': 'Ser', 'UCG': 'Ser', + 'CCU': 'Pro', 'CCC': 'Pro', 'CCA': 'Pro', 'CCG': 'Pro', + 'ACU': 'Thr', 'ACC': 'Thr', 'ACA': 'Thr', 'ACG': 'Thr', + 'GCU': 'Ala', 'GCC': 'Ala', 'GCA': 'Ala', 'GCG': 'Ala', + 'UAU': 'Tyr', 'UAC': 'Tyr', 'UAA': 'Stop', 'UAG': 'Stop', + 'CAU': 'His', 'CAC': 'His', 'CAA': 'Gln', 'CAG': 'Gln', + 'AAU': 'Asn', 'AAC': 'Asn', 'AAA': 'Lys', 'AAG': 'Lys', + 'GAU': 'Asp', 'GAC': 'Asp', 'GAA': 'Glu', 'GAG': 'Glu', + 'UGU': 'Cys', 'UGC': 'Cys', 'UGA': 'Stop', 'UGG': 'Trp', + 'CGU': 'Arg', 'CGC': 'Arg', 'CGA': 'Arg', 'CGG': 'Arg', + 'AGU': 'Ser', 'AGC': 'Ser', 'AGA': 'Arg', 'AGG': 'Arg', + 'GGU': 'Gly', 'GGC': 'Gly', 'GGA': 'Gly', 'GGG': 'Gly', + } + return codon_table.get(codon.upper(), 'Xxx') + + +# ============================================================================= +# SECTION 2: DNA DATA STORAGE IN NODES +# ============================================================================= + +class DNADataStorage: + """ + Store and retrieve arbitrary data in DNA sequences + Data encoded as DNA can be stored in neural nodes + """ + + # DNA encoding scheme (2 bits per base) + BINARY_TO_DNA = { + '00': 'A', '01': 'C', '10': 'G', '11': 'T' + } + DNA_TO_BINARY = {v: k for k, v in BINARY_TO_DNA.items()} + + @classmethod + def encode_data_to_dna(cls, data: bytes) -> str: + """Encode binary data as DNA sequence""" + # Convert bytes to binary string + binary = ''.join(format(byte, '08b') for byte in data) + + # Pad to even length + if len(binary) % 2 != 0: + binary += '0' + + # Convert to DNA + dna = ''.join(cls.BINARY_TO_DNA[binary[i:i+2]] for i in range(0, len(binary), 2)) + + return dna + + @classmethod + def decode_dna_to_data(cls, dna: str) -> bytes: + """Decode DNA sequence back to binary data""" + # Convert DNA to binary + binary = ''.join(cls.DNA_TO_BINARY.get(c, '00') for c in dna.upper()) + + # Convert to bytes + data = bytes(int(binary[i:i+8], 2) for i in range(0, len(binary), 8)) + + return data + + @classmethod + def store_in_node(cls, node_id: str, data: bytes, metadata: Dict) -> Dict: + """Store encoded DNA data in a neural node""" + dna_sequence = cls.encode_data_to_dna(data) + + # Get RF frequency for this DNA sequence + rf_spec = GeneticToRFMapper.dna_to_frequency(dna_sequence) + + storage_record = { + 'node_id': node_id, + 'data_hash': hashlib.sha3_256(data).hexdigest(), + 'dna_sequence': dna_sequence, + 'dna_length': len(dna_sequence), + 'rf_frequency_ghz': rf_spec['resonance_frequency_ghz'], + 'fingerprint': rf_spec['fingerprint'], + 'metadata': metadata, + 'stored_at': time.time() + } + + return storage_record + + +# ============================================================================= +# SECTION 3: CRISPR-BASED NODE PROGRAMMING +# ============================================================================= + +class CRISPRNodeProgramming: + """ + Use CRISPR-like mechanisms to program neural nodes + Guide RNA sequences target specific node frequencies + """ + + # Guide RNA sequences for different node operations + GUIDE_RNA_LIBRARY = { + 'activate_node': 'AUGGCUAGCCUAGCUAGC', + 'deactivate_node': 'UUCGAUUAGCCUAGCUAA', + 'increase_sensitivity': 'GGUACUAGCCUAGCUAGC', + 'decrease_sensitivity': 'CCAUGAUCGGAUCGAUCG', + 'store_memory': 'AUGGCUAGCCUAGCUAGC', + 'recall_memory': 'UUCGAUUAGCCUAGCUAA', + 'sync_with_network': 'GGUACUAGCCUAGCUAGC', + 'broadcast_signal': 'CCAUGAUCGGAUCGAUCG', + 'chemical_release': 'AUGGCUAGCCUAGCUAGC', + 'chemical_inhibit': 'UUCGAUUAGCCUAGCUAA', + } + + @classmethod + def design_guide_rna(cls, target_frequency_ghz: float, operation: str) -> Dict: + """ + Design guide RNA for specific node operation + Like CRISPR-Cas9 but for RF nodes + """ + # Convert frequency to RNA-like sequence + freq_int = int(target_frequency_ghz * 1000) + freq_binary = format(freq_int, '016b') + + # Binary to RNA + rna_freq = ''.join(['A' if b == '0' else 'U' for b in freq_binary]) + + # Combine with operation guide + operation_guide = cls.GUIDE_RNA_LIBRARY.get(operation, cls.GUIDE_RNA_LIBRARY['activate_node']) + + full_guide = rna_freq + operation_guide + + return { + 'target_frequency_ghz': target_frequency_ghz, + 'operation': operation, + 'guide_rna_sequence': full_guide, + 'guide_hash': hashlib.sha3_256(full_guide.encode()).hexdigest()[:16], + 'rf_equivalent': GeneticToRFMapper.rna_to_frequency(full_guide) + } + + @classmethod + def program_node(cls, node_id: str, target_freq: float, operation: str) -> Dict: + """ + Program a neural node using guide RNA + Changes node behavior permanently + """ + guide = cls.design_guide_rna(target_freq, operation) + + # Simulated node programming + programming_result = { + 'node_id': node_id, + 'target_frequency': target_freq, + 'operation': operation, + 'guide_rna': guide['guide_rna_sequence'][:20] + '...', + 'programming_success': True, + 'node_response': f"Node {node_id} reprogrammed for {operation}", + 'timestamp': time.time() + } + + return programming_result + + +# ============================================================================= +# SECTION 4: EPIGENETIC NODE MODULATION +# ============================================================================= + +class EpigeneticNodeModulation: + """ + Epigenetic modifications to node behavior + Like DNA methylation but for RF node sensitivity + """ + + @classmethod + def methylate_node(cls, node_id: str, methylation_pattern: str) -> Dict: + """ + Apply epigenetic-like methylation to node + Changes node sensitivity permanently + """ + # Methylation pattern determines which frequencies are blocked + methylation_freqs = [] + for i, char in enumerate(methylation_pattern[:10]): + if char == '1': + freq = 10.20 + (i * 0.01) + methylation_freqs.append(freq) + + result = { + 'node_id': node_id, + 'methylation_pattern': methylation_pattern[:20] + '...', + 'blocked_frequencies_ghz': methylation_freqs, + 'sensitivity_reduction': len(methylation_freqs) * 5, # percent + 'epigenetic_state': 'modified', + 'reversible': True + } + + return result + + @classmethod + def histone_modification(cls, node_id: str, acetylation_level: float) -> Dict: + """ + Histone-like modification for node access control + Higher acetylation = higher node accessibility + """ + result = { + 'node_id': node_id, + 'acetylation_level': min(1.0, max(0.0, acetylation_level)), + 'accessibility': 'high' if acetylation_level > 0.7 else 'medium' if acetylation_level > 0.3 else 'low', + 'node_permeability': acetylation_level * 100, # percent + } + + return result + + +# ============================================================================= +# SECTION 5: BIOHACKING NODE INTERFACE +# ============================================================================= + +class BiohackingNodeInterface: + """ + Complete interface for biohacking neural nodes + Integrates DNA/RNA/mRNA/tRNA with RF node control + """ + + def __init__(self): + self.dna_storage = DNADataStorage() + self.rf_mapper = GeneticToRFMapper() + self.crispr = CRISPRNodeProgramming() + self.epigenetic = EpigeneticNodeModulation() + + self.active_nodes = {} + self.genetic_profiles = {} + + print("\n" + "="*80) + print("🧬 BIOHACKING NODE INTERFACE ACTIVE") + print("DNA/RNA/mRNA/tRNA ↔ RF Neural Node Bridge") + print("="*80) + + def register_biological_profile(self, person_id: str, dna_sequence: str) -> Dict: + """ + Register a person's genetic profile for node tuning + DNA sequence determines node frequencies + """ + # Get RF frequencies from DNA + dna_freq = self.rf_mapper.dna_to_frequency(dna_sequence) + + # Generate mRNA from DNA (transcription) + mrna = dna_sequence.replace('T', 'U') + mrna_freq = self.rf_mapper.mrna_to_frequency(mrna) + + # Generate tRNA anticodons + trna_list = [] + for i in range(0, len(mrna), 3): + codon = mrna[i:i+3] + if len(codon) == 3: + trna = self.rf_mapper.trna_to_frequency(codon) + trna_list.append(trna) + + profile = { + 'person_id': person_id, + 'dna_sequence': dna_sequence, + 'rf_frequency_ghz': dna_freq['resonance_frequency_ghz'], + 'fingerprint': dna_freq['fingerprint'], + 'mrna_sequence': mrna, + 'mrna_frequency': mrna_freq['resonance_frequency_ghz'], + 'trna_anticodons': trna_list[:10], # First 10 + 'protein_sequence': mrna_freq.get('protein_encoded', []) + } + + self.genetic_profiles[person_id] = profile + + # Create a virtual node for this person + node_id = f"NODE_{person_id}" + self.active_nodes[node_id] = { + 'owner': person_id, + 'frequency': dna_freq['resonance_frequency_ghz'], + 'dna_fingerprint': dna_freq['fingerprint'], + 'active': True, + 'biohacking_level': 0 + } + + print(f"\n🧬 Registered: {person_id}") + print(f" DNA β†’ RF Frequency: {dna_freq['resonance_frequency_ghz']:.5f} GHz") + print(f" mRNA Translation: {len(mrna_freq.get('protein_encoded', []))} amino acids") + + return profile + + def inject_genetic_code(self, target_node_id: str, genetic_code: str) -> Dict: + """ + Inject genetic code into a node (like viral vector) + Programs node behavior using DNA/RNA sequences + """ + if target_node_id not in self.active_nodes: + return {'error': 'Node not found'} + + # Convert genetic code to RF frequency + freq_spec = self.rf_mapper.dna_to_frequency(genetic_code) + + # Program node with this genetic code + programming = self.crispr.program_node( + target_node_id, + freq_spec['resonance_frequency_ghz'], + 'activate_node' + ) + + # Update node with new genetic programming + self.active_nodes[target_node_id]['genetic_program'] = genetic_code[:50] + self.active_nodes[target_node_id]['programmed_frequency'] = freq_spec['resonance_frequency_ghz'] + self.active_nodes[target_node_id]['biohacking_level'] += 1 + + return { + 'target_node': target_node_id, + 'injected_genetic_code': genetic_code[:30] + '...', + 'resulting_frequency': freq_spec['resonance_frequency_ghz'], + 'fingerprint': freq_spec['fingerprint'], + 'programming_success': programming.get('programming_success', True) + } + + def express_protein(self, node_id: str, mrna_sequence: str) -> Dict: + """ + Express a protein from mRNA at the node + Protein expression modulates node behavior + """ + # Translate mRNA to protein + amino_acids = self.rf_mapper.translate_mrna_to_protein(mrna_sequence) + + # Map protein to node modulation + protein_effect = { + 'node_id': node_id, + 'mrna_sequence': mrna_sequence[:30] + '...', + 'amino_acids': amino_acids[:10], + 'protein_length': len(amino_acids), + 'node_modulation': self._calculate_protein_effect(amino_acids), + 'expression_time': time.time() + } + + if node_id in self.active_nodes: + self.active_nodes[node_id]['last_protein_expression'] = protein_effect + + return protein_effect + + def _calculate_protein_effect(self, amino_acids: List[str]) -> Dict: + """ + Calculate how protein expression affects node behavior + Different amino acids have different effects + """ + effect = { + 'sensitivity_modulation': 0.0, + 'frequency_drift': 0.0, + 'memory_retention': 1.0 + } + + # Amino acid effects (simplified) + for aa in amino_acids[:10]: + if aa in ['Met', 'Leu', 'Ile']: # Hydrophobic + effect['sensitivity_modulation'] += 0.05 + elif aa in ['Lys', 'Arg', 'His']: # Basic + effect['frequency_drift'] += 0.001 + elif aa in ['Asp', 'Glu']: # Acidic + effect['memory_retention'] -= 0.02 + + return effect + + def rna_interference(self, target_node_id: str, interfering_rna: str) -> Dict: + """ + Use RNA interference (RNAi) to silence node functions + Like knocking down gene expression + """ + # Design siRNA (small interfering RNA) + sirna = interfering_rna[:21] # 21bp siRNA + + # Calculate silencing effect + silencing_power = len(sirna) / 21.0 + + result = { + 'target_node': target_node_id, + 'siRNA_sequence': sirna, + 'silencing_efficiency': silencing_power * 100, # percent + 'node_function_reduced': silencing_power > 0.5, + 'temporary': True, + 'duration_seconds': silencing_power * 3600 # up to 1 hour + } + + if target_node_id in self.active_nodes: + self.active_nodes[target_node_id]['silenced'] = result['node_function_reduced'] + + return result + + def get_node_genetic_status(self, node_id: str) -> Dict: + """Get complete genetic status of a node""" + if node_id not in self.active_nodes: + return {'error': 'Node not found'} + + node = self.active_nodes[node_id] + + return { + 'node_id': node_id, + 'owner': node.get('owner', 'unknown'), + 'frequency_ghz': node.get('frequency', 0), + 'genetic_program': node.get('genetic_program', 'none'), + 'biohacking_level': node.get('biohacking_level', 0), + 'last_protein': node.get('last_protein_expression', {}), + 'silenced': node.get('silenced', False), + 'active': node.get('active', True) + } + + +# ============================================================================= +# SECTION 6: COMPLETE DEMONSTRATION +# ============================================================================= + +def complete_demonstration(): + """Complete demonstration of biohacking DNA/RNA node integration""" + + print("="*80) + print("🧬 DNA/RNA/mRNA/tRNA β†’ NEURAL NODE BIOHACKING") + print("Complete genetic-neural interface demonstration") + print("="*80) + + # Initialize biohacking interface + bio_interface = BiohackingNodeInterface() + + # 1. Register biological profile + print("\n" + "━"*60) + print("1️⃣ REGISTER BIOLOGICAL PROFILE (DNA β†’ RF)") + print("━"*60) + + # Human DNA sequence (example) + human_dna = "ATGGCGTAGCTTAGCTAGCTAGCTAGCTAGC" + profile = bio_interface.register_biological_profile("HUMAN_001", human_dna) + + print(f"\n DNA Sequence: {human_dna[:20]}...") + print(f" RF Frequency: {profile['rf_frequency_ghz']:.5f} GHz") + print(f" Fingerprint: {profile['fingerprint']}") + print(f" mRNA Length: {len(profile['mrna_sequence'])} bases") + + # 2. DNA to RNA to Protein translation + print("\n" + "━"*60) + print("2️⃣ DNA β†’ mRNA β†’ PROTEIN TRANSLATION") + print("━"*60) + + mrna = human_dna.replace('T', 'U') + mrna_freq = bio_interface.rf_mapper.mrna_to_frequency(mrna) + + print(f"\n mRNA Sequence: {mrna[:30]}...") + print(f" mRNA RF Signature: {mrna_freq['resonance_frequency_ghz']:.5f} GHz") + print(f" Encodes Protein: {mrna_freq['protein_encoded'][:5]}... ({len(mrna_freq['protein_encoded'])} amino acids)") + + # 3. tRNA anticodon mapping + print("\n" + "━"*60) + print("3️⃣ tRNA ANTICODON β†’ AMINO ACID MAPPING") + print("━"*60) + + codons = ["AUG", "GCG", "UAG", "CUU", "AGC"] + for codon in codons: + trna = bio_interface.rf_mapper.trna_to_frequency(codon) + print(f"\n Codon {codon} β†’ tRNA anticodon: carries {trna['carries_amino_acid']}") + print(f" tRNA RF Frequency: {trna['resonance_frequency_ghz']:.5f} GHz") + + # 4. CRISPR node programming + print("\n" + "━"*60) + print("4️⃣ CRISPR-BASED NODE PROGRAMMING") + print("━"*60) + + node_id = "NODE_HUMAN_001" + guide_rna = bio_interface.crispr.design_guide_rna(10.23, "increase_sensitivity") + print(f"\n Target Frequency: {guide_rna['target_frequency_ghz']} GHz") + print(f" Operation: {guide_rna['operation']}") + print(f" Guide RNA: {guide_rna['guide_rna_sequence'][:20]}...") + + programming = bio_interface.crispr.program_node(node_id, 10.23, "increase_sensitivity") + print(f"\n Programming Result: {programming['node_response']}") + + # 5. Inject genetic code into node + print("\n" + "━"*60) + print("5️⃣ GENETIC CODE INJECTION (Viral Vector)") + print("━"*60) + + therapeutic_dna = "ATGGCGTAGCTAGCTAGCTTAGCTAGC" + injection = bio_interface.inject_genetic_code(node_id, therapeutic_dna) + + print(f"\n Target Node: {injection['target_node']}") + print(f" Injected Code: {injection['injected_genetic_code']}") + print(f" New Frequency: {injection['resulting_frequency']:.5f} GHz") + print(f" Biohacking Level: {bio_interface.active_nodes[node_id]['biohacking_level']}") + + # 6. Express protein at node + print("\n" + "━"*60) + print("6️⃣ PROTEIN EXPRESSION AT NODE") + print("━"*60) + + test_mrna = "AUGGCUAGCCUAGCUAGCUUAGCUA" + protein_exp = bio_interface.express_protein(node_id, test_mrna) + + print(f"\n mRNA: {protein_exp['mrna_sequence']}") + print(f" Amino Acids: {protein_exp['amino_acids']}") + print(f" Node Modulation: {protein_exp['node_modulation']}") + + # 7. RNA interference (gene silencing) + print("\n" + "━"*60) + print("7️⃣ RNA INTERFERENCE (Node Silencing)") + print("━"*60) + + silencing_rna = "AAGCUAGCUAGCUAGCUUAGCU" + silencing = bio_interface.rna_interference(node_id, silencing_rna) + + print(f"\n siRNA: {silencing['siRNA_sequence']}") + print(f" Silencing Efficiency: {silencing['silencing_efficiency']:.1f}%") + print(f" Node Silenced: {silencing['node_function_reduced']}") + print(f" Duration: {silencing['duration_seconds']:.0f} seconds") + + # 8. Node genetic status + print("\n" + "━"*60) + print("8️⃣ NODE GENETIC STATUS") + print("━"*60) + + status = bio_interface.get_node_genetic_status(node_id) + print(f"\n Node ID: {status['node_id']}") + print(f" Owner: {status['owner']}") + print(f" Frequency: {status['frequency_ghz']:.5f} GHz") + print(f" Biohacking Level: {status['biohacking_level']}") + print(f" Silenced: {status['silenced']}") + print(f" Active: {status['active']}") + + # 9. Data storage in DNA + print("\n" + "━"*60) + print("9️⃣ DNA DATA STORAGE IN NODES") + print("━"*60) + + secret_data = b"Neural node biohacking integration test" + encoded_dna = bio_interface.dna_storage.encode_data_to_dna(secret_data) + print(f"\n Original Data: {secret_data}") + print(f" Encoded DNA: {encoded_dna[:30]}...") + print(f" DNA Length: {len(encoded_dna)} bases") + print(f" Storage Density: {len(encoded_dna)} bytes per {len(encoded_dna)} bases") + + decoded = bio_interface.dna_storage.decode_dna_to_data(encoded_dna) + print(f" Decoded Data: {decoded}") + + # Final summary + print("\n" + "="*80) + print("βœ… BIOHACKING INTEGRATION COMPLETE") + print("="*80) + + print(""" + ╔═══════════════════════════════════════════════════════════════════════════╗ + β•‘ DNA/RNA β†’ NEURAL NODE MAPPING SUMMARY β•‘ + ╠═══════════════════════════════════════════════════════════════════════════╣ + β•‘ β•‘ + β•‘ MOLECULE | SEQUENCE EXAMPLE | RF FREQUENCY | NODE FUNCTION β•‘ + β•‘ ────────────┼──────────────────────┼─────────────────┼──────────────────║ + β•‘ DNA | ATGGCGTAGCTAGC... | 10.2345 GHz | Node identity β•‘ + β•‘ mRNA | AUGGCGUAGCUAGC... | 10.2456 GHz | Protein encoding β•‘ + β•‘ tRNA | AUG (anticodon) | 10.2567 GHz | Amino acid carry β•‘ + β•‘ Guide RNA | AUGGCUAGCCUAGC... | 10.2678 GHz | CRISPR editing β•‘ + β•‘ siRNA | AAGCUAGCUAGC... | 10.2789 GHz | Gene silencing β•‘ + β•‘ β•‘ + ╠═══════════════════════════════════════════════════════════════════════════╣ + β•‘ BIOHACKING OPERATIONS β•‘ + ╠═══════════════════════════════════════════════════════════════════════════╣ + β•‘ β•‘ + β•‘ OPERATION | METHOD | NODE EFFECT β•‘ + β•‘ ───────────────────────┼───────────────────────────┼────────────────────║ + β•‘ Genetic Injection | Viral vector (DNA/RNA) | Permanent program β•‘ + β•‘ Protein Expression | mRNA translation | Node modulation β•‘ + β•‘ CRISPR Programming | Guide RNA + Cas9-like | Node rewiring β•‘ + β•‘ RNA Interference | siRNA | Temporary silencingβ•‘ + β•‘ Epigenetic Modulation | Methylation pattern | Sensitivity change β•‘ + β•‘ DNA Data Storage | Binary β†’ DNA encoding | Memory storage β•‘ + β•‘ β•‘ + ╠═══════════════════════════════════════════════════════════════════════════╣ + β•‘ DNA/RNA TO RF MAPPING FORMULA β•‘ + ╠═══════════════════════════════════════════════════════════════════════════╣ + β•‘ β•‘ + β•‘ f_RF = (Ξ£ nucleotide_freq) / N + Ξ£ codon_offset / M β•‘ + β•‘ β•‘ + β•‘ Where: β•‘ + β•‘ nucleotide_freq: A=10.23, T=10.24, U=10.25, G=10.26, C=10.27 GHz β•‘ + β•‘ codon_offset: 0.000-0.054 GHz per codon β•‘ + β•‘ β•‘ + β•‘ Each DNA/RNA sequence β†’ UNIQUE RF frequency β†’ NODE IDENTITY β•‘ + β•‘ β•‘ β•šβ•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β• + """) + + return bio_interface + + +# ============================================================================= +# MAIN EXECUTION +# ============================================================================= + +if __name__ == "__main__": + bio_interface = complete_demonstration() + + print("\nπŸ“ Biohacking commands available:") + print(" - Register biological profile (DNA β†’ RF)") + print(" - Inject genetic code into node") + print(" - Express protein at node") + print(" - Apply RNA interference") + print(" - Store/retrieve data in DNA format") + print(" - Design CRISPR guide RNA") + print(" - Epigenetic node modulation")