MSO Base 4 Demonstration: Deterministic Geometric Resolution of FASTA Sequences (NCBI OV986001.1)
Author: Yannick Fouconnier | August 2026.
MSO Reference: 10.5281/zenodo.19385043
Data Source: NCBI Nucleotide Archive — Accession OV986001.1
Input Data (NCBI Raw FASTA File) Extracted genomic sequence from the public NCBI repository:
OV986001.1 Genomic Sequence Extract (NCBI Public Repository)
ATGCGATCGATCGATCGATCGATCGATCGATCGATCGATCGATCGATCGATCGATCStep 1: Mapping to the Native Base-4 Vector Alphabet Classical probabilistic bioinformatics treats sequences as ASCII strings subject to variance approximations. The MSO Kernel executes an immediate deterministic vector projection:
A (Adenine) → A (00₂)
C (Cytosine) → B (01₂)
G (Guanine) → C (10₂)
T (Thymine) → 0 (11₂)
Generated MSO Vectorial Strand:
[A, 0, C, B, C, A, 0, B, C, A, 0, B, C, A, 0, B, C, A, 0, B, C, A, 0, B, ...]Step 2: Geometric Invariant & Trajectory on the D₂₄ Lattice For a k-mer size of k = 4, sliding cellular windows are directly projected as discrete state coordinates onto the D₂₄ lattice:
1st k-mer (ATGC): [A, 0, C, B] → Initial phase coordinate Φ₀.
2nd k-mer (TGCA): [0, C, B, A] → Orthogonal geometric translation to the adjacent lattice node.
The invariant operator ICN ≈ 1.0418 fixes the exact metric of each state transition without statistical bias.
Step 3: Deterministic Isolation (Substitutions vs. Indels)
Guarantees & Algorithmic Summary
Zero Entropy Debt (E_debt = 0): Zero information loss or cumulative noise over length N.
Linear Time Complexity O(N): Direct linear execution by eliminating heavy covariance matrices and Monte-Carlo simulations.
Absolute Reproducibility: Deterministic validation applicable to any k-mer analysis pipeline without relying on asymptotic concentration bounds.
