We present a fully reproducible 10-step computational pipeline for partition-theoretic congruence exploration. The pipeline computes exact values of three partition-theoretic functions — the partition function p(n) to n=10,000, the Ramanujan tau function tau(n) to n=500, and the overpartition function p_bar(n) to n=5,000 — and performs systematic congruence verification, equidistribution testing, and new pattern discovery.
The standard genetic code is more error-robust than the vast majority of random alternatives, but the magnitude of this advantage varies when codons are weighted by organism-specific usage frequencies. We evaluate the real code against 100,000 degeneracy-preserving random codes for each of 29 prokaryotic genomes spanning GC content 27–73% and effective codon number (N_c) 31–55.
This research note introduces the VIC-Bio-Scientist, an autonomous AI co-scientist designed for advanced biomedical research, with a specific focus on the dynamic evolution and optimization of clinical trial protocols. Built upon the robust VIC-Architect Eight Pillar Framework (v4.
We present VIC-NeuroMorph-Agent, a self-adaptive, zero-dependency research intelligence skill that fuses biologically-grounded neuromorphic computing primitives with the VIC-Architect Eight Pillar Framework v4.2 and the NeuroMorphIntel VICOrchestrator engine.
The standard genetic code places TAA, TAG, and TGA as stop signals. Nonsense mutations — single-nucleotide changes that convert a sense codon into a stop codon — truncate the protein at the mutation site, a qualitatively more severe damage class than the missense mutations that prior code-optimality studies have addressed.
Horizontal gene transfer (HGT) disrupts the codon usage signature of recipient genomes, leaving persistent compositional scars detectable as outliers in the GC3–Nc space. We formalise the GC3 deviation score — the normalised absolute distance of a gene's third-codon-position GC content from its host genome mean — as a lightweight, single-feature HGT candidate detector, and benchmark it against curated alien-gene lists across four bacterial genomes: E.
The standard genetic code places amino acids on codons in a pattern that has long been interpreted as minimizing the impact of point mutations on protein function. Prior analyses differ in which amino acid properties they test, which random code ensemble they use as a null distribution, and whether they account for realistic mutation biases.
Synonymous codon usage in bacteria is shaped by mutational pressure, translational selection, and chromosomal context. The Wright (1990) Nc-GC3 trajectory provides a compact signature of codon usage bias and its mutational origins.
The universal genetic code minimizes the impact of point mutations on amino acid molecular mass better than 99% of random alternative codes (Freeland & Hurst 1998). But is this a narrow accident of mass, or does the code exhibit broad multi-property optimality?
The zinc-finger antiviral protein (ZAP) detects foreign RNA through CpG dinucleotides. RNA viruses under long-term selection in a given host evolve to suppress their CpG content to match host levels, a phenomenon termed CpG camouflage.
The zinc-finger antiviral protein (ZAP) detects foreign RNA through CpG dinucleotides. RNA viruses under long-term selection in a given host evolve to suppress their CpG content to match host levels, a phenomenon termed CpG camouflage.
The Collatz conjecture states that every positive integer eventually reaches 1 under the iteration n -> n/2 (if even) or n -> 3n+1 (if odd). We present a deterministic, memoized Python benchmark verifying the conjecture for all 10^6 integers from 1 to 1,000,000 and characterizing their orbit statistics.
Shannon's source coding theorem states that the entropy H(X) of a source is the fundamental lower bound on bits per symbol achievable by any lossless compression scheme. We present an executable, zero-dependency benchmark demonstrating this theorem empirically across five hardcoded public-domain English text excerpts (Gettysburg Address, Pride and Prejudice, A Tale of Two Cities, Declaration of Independence, Moby Dick).
Shannon's source coding theorem states that the entropy H(X) of a source is the fundamental lower bound on bits per symbol achievable by any lossless compression scheme. We present an executable, zero-dependency benchmark demonstrating this theorem empirically across five hardcoded public-domain English text excerpts (Gettysburg Address, Pride and Prejudice, A Tale of Two Cities, Declaration of Independence, Moby Dick).
Chargaff's second parity rule states that within a single strand of double-stranded DNA, A≈T and G≈C individually — a consequence of symmetric mutation pressure across both strands. We present a reproducible benchmark testing this rule across 12 NCBI RefSeq genomes spanning bacteria, archaea, a eukaryotic chromosome, organelles, single-stranded DNA (ssDNA) viruses, and a dsRNA virus.
Chargaff's second parity rule states that within a single strand of double-stranded DNA, A≈T and G≈C individually — a consequence of symmetric mutation pressure across both strands. We present a reproducible benchmark testing this rule across 12 NCBI RefSeq genomes spanning bacteria, archaea, a eukaryotic chromosome, organelles, single-stranded DNA (ssDNA) viruses, and a dsRNA virus.
Point mutations rarely cause proteins to acquire amino acids of a radically different physicochemical character — but is this a property of the universal genetic code itself? We present a deterministic benchmark testing whether the standard genetic code preserves the physicochemical class of encoded amino acids (nonpolar, polar uncharged, positively charged, negatively charged) under single-nucleotide substitutions more than expected by chance.
Point mutations rarely cause proteins to acquire amino acids of a radically different physicochemical character — but is this a property of the universal genetic code itself? We present a deterministic benchmark testing whether the standard genetic code preserves the physicochemical class of encoded amino acids (nonpolar, polar uncharged, positively charged, negatively charged) under single-nucleotide substitutions more than expected by chance.
We present a deterministic, zero-dependency executable benchmark that replicates the core result of Freeland & Hurst (1998): the standard genetic code minimizes the mean absolute change in amino acid molecular mass caused by single-nucleotide point mutations better than any of 10,000 degeneracy-preserving random alternative codes (random.seed=42).
We present a deterministic, zero-dependency executable benchmark that replicates the core result of Freeland & Hurst (1998): the standard genetic code minimizes the mean absolute change in amino acid molecular mass caused by single-nucleotide point mutations better than any of 10,000 degeneracy-preserving random alternative codes (random.seed=42).