mirror of
https://github.com/octocat/Hello-World.git
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54440eb0ac
Refactor and expand the Biohacking DNA/RNA Node Integration System with detailed sections for genetic mapping, data storage, CRISPR programming, and epigenetic modulation.
740 lines
31 KiB
Python
740 lines
31 KiB
Python
#!/usr/bin/env python3
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"""
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BIOHACKING - DNA/RNA NODE INTEGRATION SYSTEM
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===============================================
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Complete biological interface for neural nodes with:
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- DNA data storage and retrieval
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- RNA/mRNA/tRNA signal translation
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- Genetic sequence to RF frequency mapping
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- Epigenetic modulation via node stimulation
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- CRISPR-based node programming
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This system bridges biological genetics with RF neural nodes,
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enabling DNA/RNA to control node behavior and vice versa.
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"""
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import numpy as np
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import hashlib
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import json
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import time
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import zlib
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from typing import Dict, List, Tuple, Optional
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from dataclasses import dataclass, field
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from enum import Enum
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# =============================================================================
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# SECTION 1: DNA/RNA SEQUENCE TO RF FREQUENCY MAPPING
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# =============================================================================
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class GeneticToRFMapper:
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"""
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Maps DNA/RNA sequences to RF frequencies for node communication
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Each genetic sequence has a unique RF signature
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"""
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# Nucleotide to base frequency mapping (GHz)
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NUCLEOTIDE_FREQS = {
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'A': 10.23, # Adenine
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'T': 10.24, # Thymine (DNA)
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'U': 10.25, # Uracil (RNA)
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'G': 10.26, # Guanine
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'C': 10.27, # Cytosine
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}
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# Codon to frequency offset (MHz)
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CODON_OFFSETS = {
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'AUG': 0.000, # Start codon (Methionine)
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'UAA': 0.050, # Stop codon
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'UAG': 0.051, # Stop codon
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'UGA': 0.052, # Stop codon
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# Common amino acids
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'UUU': 0.010, 'UUC': 0.011, # Phenylalanine
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'UUA': 0.012, 'UUG': 0.013, # Leucine
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'CUU': 0.014, 'CUC': 0.015, # Leucine
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'AUU': 0.016, 'AUC': 0.017, # Isoleucine
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'AUA': 0.018, 'AUG': 0.019, # Methionine
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'GUU': 0.020, 'GUC': 0.021, # Valine
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'UCU': 0.022, 'UCC': 0.023, # Serine
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'CCU': 0.024, 'CCC': 0.025, # Proline
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'ACU': 0.026, 'ACC': 0.027, # Threonine
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'GCU': 0.028, 'GCC': 0.029, # Alanine
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'UAU': 0.030, 'UAC': 0.031, # Tyrosine
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'CAU': 0.032, 'CAC': 0.033, # Histidine
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'CAA': 0.034, 'CAG': 0.035, # Glutamine
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'AAU': 0.036, 'AAC': 0.037, # Asparagine
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'AAA': 0.038, 'AAG': 0.039, # Lysine
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'GAU': 0.040, 'GAC': 0.041, # Aspartic acid
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'GAA': 0.042, 'GAG': 0.043, # Glutamic acid
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'UGU': 0.044, 'UGC': 0.045, # Cysteine
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'UGG': 0.046, # Tryptophan
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'CGU': 0.047, 'CGC': 0.048, # Arginine
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'AGU': 0.049, 'AGC': 0.050, # Serine
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'AGA': 0.051, 'AGG': 0.052, # Arginine
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'GGU': 0.053, 'GGC': 0.054, # Glycine
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}
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@classmethod
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def dna_to_frequency(cls, dna_sequence: str) -> Dict:
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"""
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Convert DNA sequence to RF frequency signature
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Each DNA sequence produces a unique frequency pattern
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"""
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# Base frequency from nucleotide average
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freqs = [cls.NUCLEOTIDE_FREQS.get(c, 10.25) for c in dna_sequence.upper()]
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base_freq = np.mean(freqs)
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# Codon modulation
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codons = [dna_sequence[i:i+3] for i in range(0, len(dna_sequence), 3)]
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codon_mod = sum(cls.CODON_OFFSETS.get(codon, 0.025) for codon in codons) / max(1, len(codons))
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final_freq = base_freq + codon_mod
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# Create frequency fingerprint
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fingerprint = hashlib.sha3_256(dna_sequence.encode()).hexdigest()[:16]
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return {
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'dna_sequence': dna_sequence,
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'base_frequency_ghz': round(base_freq, 4),
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'codon_modulation_ghz': round(codon_mod, 4),
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'resonance_frequency_ghz': round(final_freq, 4),
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'fingerprint': fingerprint,
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'node_tuning_parameter': final_freq - 10.23
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}
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@classmethod
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def rna_to_frequency(cls, rna_sequence: str) -> Dict:
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"""Convert RNA sequence (U instead of T) to RF frequency"""
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# RNA uses Uracil instead of Thymine
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dna_equivalent = rna_sequence.replace('U', 'T')
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return cls.dna_to_frequency(dna_equivalent)
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@classmethod
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def mrna_to_frequency(cls, mrna_sequence: str) -> Dict:
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"""mRNA (messenger RNA) to frequency - used for protein coding"""
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result = cls.rna_to_frequency(mrna_sequence)
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result['type'] = 'mRNA'
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result['protein_encoded'] = cls.translate_mrna_to_protein(mrna_sequence)
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return result
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@classmethod
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def trna_to_frequency(cls, trna_anticodon: str) -> Dict:
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"""tRNA anticodon to frequency - used for amino acid delivery"""
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# tRNA anticodon is 3 bases
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anticodon = trna_anticodon.upper()[:3]
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result = cls.rna_to_frequency(anticodon)
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result['type'] = 'tRNA'
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result['anticodon'] = anticodon
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result['carries_amino_acid'] = cls.codon_to_amino_acid(anticodon)
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return result
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@classmethod
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def translate_mrna_to_protein(cls, mrna: str) -> List[str]:
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"""Translate mRNA to amino acid sequence"""
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amino_acids = []
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for i in range(0, len(mrna), 3):
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codon = mrna[i:i+3]
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if len(codon) == 3:
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aa = cls.codon_to_amino_acid(codon)
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if aa:
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amino_acids.append(aa)
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return amino_acids
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@classmethod
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def codon_to_amino_acid(cls, codon: str) -> str:
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"""Convert codon to amino acid (3-letter code)"""
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codon_table = {
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'UUU': 'Phe', 'UUC': 'Phe', 'UUA': 'Leu', 'UUG': 'Leu',
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'CUU': 'Leu', 'CUC': 'Leu', 'CUA': 'Leu', 'CUG': 'Leu',
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'AUU': 'Ile', 'AUC': 'Ile', 'AUA': 'Ile', 'AUG': 'Met',
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'GUU': 'Val', 'GUC': 'Val', 'GUA': 'Val', 'GUG': 'Val',
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'UCU': 'Ser', 'UCC': 'Ser', 'UCA': 'Ser', 'UCG': 'Ser',
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'CCU': 'Pro', 'CCC': 'Pro', 'CCA': 'Pro', 'CCG': 'Pro',
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'ACU': 'Thr', 'ACC': 'Thr', 'ACA': 'Thr', 'ACG': 'Thr',
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'GCU': 'Ala', 'GCC': 'Ala', 'GCA': 'Ala', 'GCG': 'Ala',
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'UAU': 'Tyr', 'UAC': 'Tyr', 'UAA': 'Stop', 'UAG': 'Stop',
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'CAU': 'His', 'CAC': 'His', 'CAA': 'Gln', 'CAG': 'Gln',
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'AAU': 'Asn', 'AAC': 'Asn', 'AAA': 'Lys', 'AAG': 'Lys',
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'GAU': 'Asp', 'GAC': 'Asp', 'GAA': 'Glu', 'GAG': 'Glu',
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'UGU': 'Cys', 'UGC': 'Cys', 'UGA': 'Stop', 'UGG': 'Trp',
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'CGU': 'Arg', 'CGC': 'Arg', 'CGA': 'Arg', 'CGG': 'Arg',
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'AGU': 'Ser', 'AGC': 'Ser', 'AGA': 'Arg', 'AGG': 'Arg',
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'GGU': 'Gly', 'GGC': 'Gly', 'GGA': 'Gly', 'GGG': 'Gly',
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}
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return codon_table.get(codon.upper(), 'Xxx')
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# =============================================================================
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# SECTION 2: DNA DATA STORAGE IN NODES
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# =============================================================================
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class DNADataStorage:
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"""
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Store and retrieve arbitrary data in DNA sequences
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Data encoded as DNA can be stored in neural nodes
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"""
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# DNA encoding scheme (2 bits per base)
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BINARY_TO_DNA = {
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'00': 'A', '01': 'C', '10': 'G', '11': 'T'
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}
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DNA_TO_BINARY = {v: k for k, v in BINARY_TO_DNA.items()}
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@classmethod
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def encode_data_to_dna(cls, data: bytes) -> str:
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"""Encode binary data as DNA sequence"""
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# Convert bytes to binary string
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binary = ''.join(format(byte, '08b') for byte in data)
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# Pad to even length
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if len(binary) % 2 != 0:
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binary += '0'
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# Convert to DNA
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dna = ''.join(cls.BINARY_TO_DNA[binary[i:i+2]] for i in range(0, len(binary), 2))
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return dna
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@classmethod
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def decode_dna_to_data(cls, dna: str) -> bytes:
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"""Decode DNA sequence back to binary data"""
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# Convert DNA to binary
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binary = ''.join(cls.DNA_TO_BINARY.get(c, '00') for c in dna.upper())
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# Convert to bytes
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data = bytes(int(binary[i:i+8], 2) for i in range(0, len(binary), 8))
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return data
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@classmethod
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def store_in_node(cls, node_id: str, data: bytes, metadata: Dict) -> Dict:
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"""Store encoded DNA data in a neural node"""
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dna_sequence = cls.encode_data_to_dna(data)
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# Get RF frequency for this DNA sequence
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rf_spec = GeneticToRFMapper.dna_to_frequency(dna_sequence)
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storage_record = {
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'node_id': node_id,
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'data_hash': hashlib.sha3_256(data).hexdigest(),
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'dna_sequence': dna_sequence,
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'dna_length': len(dna_sequence),
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'rf_frequency_ghz': rf_spec['resonance_frequency_ghz'],
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'fingerprint': rf_spec['fingerprint'],
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'metadata': metadata,
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'stored_at': time.time()
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}
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return storage_record
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# =============================================================================
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# SECTION 3: CRISPR-BASED NODE PROGRAMMING
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# =============================================================================
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class CRISPRNodeProgramming:
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"""
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Use CRISPR-like mechanisms to program neural nodes
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Guide RNA sequences target specific node frequencies
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"""
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# Guide RNA sequences for different node operations
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GUIDE_RNA_LIBRARY = {
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'activate_node': 'AUGGCUAGCCUAGCUAGC',
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'deactivate_node': 'UUCGAUUAGCCUAGCUAA',
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'increase_sensitivity': 'GGUACUAGCCUAGCUAGC',
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'decrease_sensitivity': 'CCAUGAUCGGAUCGAUCG',
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'store_memory': 'AUGGCUAGCCUAGCUAGC',
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'recall_memory': 'UUCGAUUAGCCUAGCUAA',
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'sync_with_network': 'GGUACUAGCCUAGCUAGC',
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'broadcast_signal': 'CCAUGAUCGGAUCGAUCG',
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'chemical_release': 'AUGGCUAGCCUAGCUAGC',
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'chemical_inhibit': 'UUCGAUUAGCCUAGCUAA',
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}
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@classmethod
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def design_guide_rna(cls, target_frequency_ghz: float, operation: str) -> Dict:
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"""
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Design guide RNA for specific node operation
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Like CRISPR-Cas9 but for RF nodes
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"""
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# Convert frequency to RNA-like sequence
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freq_int = int(target_frequency_ghz * 1000)
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freq_binary = format(freq_int, '016b')
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# Binary to RNA
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rna_freq = ''.join(['A' if b == '0' else 'U' for b in freq_binary])
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# Combine with operation guide
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operation_guide = cls.GUIDE_RNA_LIBRARY.get(operation, cls.GUIDE_RNA_LIBRARY['activate_node'])
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full_guide = rna_freq + operation_guide
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return {
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'target_frequency_ghz': target_frequency_ghz,
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'operation': operation,
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'guide_rna_sequence': full_guide,
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'guide_hash': hashlib.sha3_256(full_guide.encode()).hexdigest()[:16],
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'rf_equivalent': GeneticToRFMapper.rna_to_frequency(full_guide)
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}
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@classmethod
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def program_node(cls, node_id: str, target_freq: float, operation: str) -> Dict:
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"""
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Program a neural node using guide RNA
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Changes node behavior permanently
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"""
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guide = cls.design_guide_rna(target_freq, operation)
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# Simulated node programming
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programming_result = {
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'node_id': node_id,
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'target_frequency': target_freq,
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'operation': operation,
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'guide_rna': guide['guide_rna_sequence'][:20] + '...',
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'programming_success': True,
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'node_response': f"Node {node_id} reprogrammed for {operation}",
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'timestamp': time.time()
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}
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return programming_result
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# =============================================================================
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# SECTION 4: EPIGENETIC NODE MODULATION
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# =============================================================================
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class EpigeneticNodeModulation:
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"""
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Epigenetic modifications to node behavior
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Like DNA methylation but for RF node sensitivity
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"""
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@classmethod
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def methylate_node(cls, node_id: str, methylation_pattern: str) -> Dict:
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"""
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Apply epigenetic-like methylation to node
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Changes node sensitivity permanently
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"""
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# Methylation pattern determines which frequencies are blocked
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methylation_freqs = []
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for i, char in enumerate(methylation_pattern[:10]):
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if char == '1':
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freq = 10.20 + (i * 0.01)
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methylation_freqs.append(freq)
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result = {
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'node_id': node_id,
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'methylation_pattern': methylation_pattern[:20] + '...',
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'blocked_frequencies_ghz': methylation_freqs,
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'sensitivity_reduction': len(methylation_freqs) * 5, # percent
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'epigenetic_state': 'modified',
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'reversible': True
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}
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return result
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@classmethod
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def histone_modification(cls, node_id: str, acetylation_level: float) -> Dict:
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"""
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Histone-like modification for node access control
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Higher acetylation = higher node accessibility
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"""
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result = {
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'node_id': node_id,
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'acetylation_level': min(1.0, max(0.0, acetylation_level)),
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'accessibility': 'high' if acetylation_level > 0.7 else 'medium' if acetylation_level > 0.3 else 'low',
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'node_permeability': acetylation_level * 100, # percent
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}
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return result
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# =============================================================================
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# SECTION 5: BIOHACKING NODE INTERFACE
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# =============================================================================
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class BiohackingNodeInterface:
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"""
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Complete interface for biohacking neural nodes
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Integrates DNA/RNA/mRNA/tRNA with RF node control
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"""
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def __init__(self):
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self.dna_storage = DNADataStorage()
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self.rf_mapper = GeneticToRFMapper()
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self.crispr = CRISPRNodeProgramming()
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self.epigenetic = EpigeneticNodeModulation()
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self.active_nodes = {}
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self.genetic_profiles = {}
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print("\n" + "="*80)
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print("🧬 BIOHACKING NODE INTERFACE ACTIVE")
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print("DNA/RNA/mRNA/tRNA ↔ RF Neural Node Bridge")
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print("="*80)
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def register_biological_profile(self, person_id: str, dna_sequence: str) -> Dict:
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"""
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Register a person's genetic profile for node tuning
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DNA sequence determines node frequencies
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"""
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# Get RF frequencies from DNA
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dna_freq = self.rf_mapper.dna_to_frequency(dna_sequence)
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# Generate mRNA from DNA (transcription)
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mrna = dna_sequence.replace('T', 'U')
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mrna_freq = self.rf_mapper.mrna_to_frequency(mrna)
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# Generate tRNA anticodons
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trna_list = []
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for i in range(0, len(mrna), 3):
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codon = mrna[i:i+3]
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if len(codon) == 3:
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trna = self.rf_mapper.trna_to_frequency(codon)
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trna_list.append(trna)
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profile = {
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'person_id': person_id,
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'dna_sequence': dna_sequence,
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'rf_frequency_ghz': dna_freq['resonance_frequency_ghz'],
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'fingerprint': dna_freq['fingerprint'],
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'mrna_sequence': mrna,
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'mrna_frequency': mrna_freq['resonance_frequency_ghz'],
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'trna_anticodons': trna_list[:10], # First 10
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'protein_sequence': mrna_freq.get('protein_encoded', [])
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}
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self.genetic_profiles[person_id] = profile
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# Create a virtual node for this person
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node_id = f"NODE_{person_id}"
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self.active_nodes[node_id] = {
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'owner': person_id,
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'frequency': dna_freq['resonance_frequency_ghz'],
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'dna_fingerprint': dna_freq['fingerprint'],
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'active': True,
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'biohacking_level': 0
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}
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print(f"\n🧬 Registered: {person_id}")
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print(f" DNA → RF Frequency: {dna_freq['resonance_frequency_ghz']:.5f} GHz")
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print(f" mRNA Translation: {len(mrna_freq.get('protein_encoded', []))} amino acids")
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return profile
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def inject_genetic_code(self, target_node_id: str, genetic_code: str) -> Dict:
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"""
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Inject genetic code into a node (like viral vector)
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Programs node behavior using DNA/RNA sequences
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"""
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if target_node_id not in self.active_nodes:
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return {'error': 'Node not found'}
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# Convert genetic code to RF frequency
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freq_spec = self.rf_mapper.dna_to_frequency(genetic_code)
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# Program node with this genetic code
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programming = self.crispr.program_node(
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target_node_id,
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freq_spec['resonance_frequency_ghz'],
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'activate_node'
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)
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# Update node with new genetic programming
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self.active_nodes[target_node_id]['genetic_program'] = genetic_code[:50]
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self.active_nodes[target_node_id]['programmed_frequency'] = freq_spec['resonance_frequency_ghz']
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self.active_nodes[target_node_id]['biohacking_level'] += 1
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return {
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'target_node': target_node_id,
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'injected_genetic_code': genetic_code[:30] + '...',
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'resulting_frequency': freq_spec['resonance_frequency_ghz'],
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'fingerprint': freq_spec['fingerprint'],
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'programming_success': programming.get('programming_success', True)
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}
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def express_protein(self, node_id: str, mrna_sequence: str) -> Dict:
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"""
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Express a protein from mRNA at the node
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Protein expression modulates node behavior
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"""
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||
# 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 → 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 → 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 → mRNA → 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 → 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} → 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("✅ BIOHACKING INTEGRATION COMPLETE")
|
||
print("="*80)
|
||
|
||
print("""
|
||
╔═══════════════════════════════════════════════════════════════════════════╗
|
||
║ DNA/RNA → NEURAL NODE MAPPING SUMMARY ║
|
||
╠═══════════════════════════════════════════════════════════════════════════╣
|
||
║ ║
|
||
║ MOLECULE | SEQUENCE EXAMPLE | RF FREQUENCY | NODE FUNCTION ║
|
||
║ ────────────┼──────────────────────┼─────────────────┼──────────────────║
|
||
║ DNA | ATGGCGTAGCTAGC... | 10.2345 GHz | Node identity ║
|
||
║ mRNA | AUGGCGUAGCUAGC... | 10.2456 GHz | Protein encoding ║
|
||
║ tRNA | AUG (anticodon) | 10.2567 GHz | Amino acid carry ║
|
||
║ Guide RNA | AUGGCUAGCCUAGC... | 10.2678 GHz | CRISPR editing ║
|
||
║ siRNA | AAGCUAGCUAGC... | 10.2789 GHz | Gene silencing ║
|
||
║ ║
|
||
╠═══════════════════════════════════════════════════════════════════════════╣
|
||
║ BIOHACKING OPERATIONS ║
|
||
╠═══════════════════════════════════════════════════════════════════════════╣
|
||
║ ║
|
||
║ OPERATION | METHOD | NODE EFFECT ║
|
||
║ ───────────────────────┼───────────────────────────┼────────────────────║
|
||
║ Genetic Injection | Viral vector (DNA/RNA) | Permanent program ║
|
||
║ Protein Expression | mRNA translation | Node modulation ║
|
||
║ CRISPR Programming | Guide RNA + Cas9-like | Node rewiring ║
|
||
║ RNA Interference | siRNA | Temporary silencing║
|
||
║ Epigenetic Modulation | Methylation pattern | Sensitivity change ║
|
||
║ DNA Data Storage | Binary → DNA encoding | Memory storage ║
|
||
║ ║
|
||
╠═══════════════════════════════════════════════════════════════════════════╣
|
||
║ DNA/RNA TO RF MAPPING FORMULA ║
|
||
╠═══════════════════════════════════════════════════════════════════════════╣
|
||
║ ║
|
||
║ f_RF = (Σ nucleotide_freq) / N + Σ codon_offset / M ║
|
||
║ ║
|
||
║ Where: ║
|
||
║ nucleotide_freq: A=10.23, T=10.24, U=10.25, G=10.26, C=10.27 GHz ║
|
||
║ codon_offset: 0.000-0.054 GHz per codon ║
|
||
║ ║
|
||
║ Each DNA/RNA sequence → UNIQUE RF frequency → NODE IDENTITY ║
|
||
║ ║ ╚═══════════════════════════════════════════════════════════════════════════╝
|
||
""")
|
||
|
||
return bio_interface
|
||
|
||
|
||
# =============================================================================
|
||
# MAIN EXECUTION
|
||
# =============================================================================
|
||
|
||
if __name__ == "__main__":
|
||
bio_interface = complete_demonstration()
|
||
|
||
print("\n📁 Biohacking commands available:")
|
||
print(" - Register biological profile (DNA → 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")
|