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Published October 12, 2025 | Version v0.8.

Mutation by Natural Dominance (TMD): a testable framework for evolution and the origin of life — software & data (v0.8)

Description

Short description

Plain summary. Mutation by Natural Dominance (TMD) is a testable framework for predicting which adaptive genetic route appears first when several solutions are available. The core rule is simple: the chance that a route wins first is proportional to its mutation rate (μ) × genome accessibility (A) × fixation probability (F). This record releases an execution‑grade toolkit (code, docs, figures) to run preregistered tests (G1–G3), design studies, and reproduce the plots shown in the accompanying materials.

 

Long description

# Mutation by Natural Dominance (TMD) — Zenodo record (v0.8)

 

**Status**: testable framework (pre‑theory). When preregistered gates G1–G3 pass, cite as “The Theory of Mutation by Natural Dominance (TMD).”

 

**Core idea (plain language)**

Evolution often follows the *easiest* genetic path. Some mutations occur more often (chemistry), and some genome regions are more exposed (architecture). The route with the largest **MDI = μ × A × F** tends to win first.

 

**What’s in this record**

- **Software kits**: `TMD_kit_v0_2.zip` … `TMD_kit_v0_8.zip` (pipelines for G1–G5, power calculators, dominance/ridge plots, replicator–mutator and Poisson‑race simulators).

- **Figures bundle**: publication‑ready PNGs (power surfaces, dominance ridge, timecourses, first‑fix histograms).

- **Design data**: example JSON/CSV templates; power and ridge tables.

- **Docs**: whitepaper draft, submission pack, explainer, prereg blocks, figure captions.

 

**How to run (one‑liners)**

- G3 “who fixes first?”: `python pipelines/gillespie_first_fix.py 5e-3 2e-3 5000`

- CTMC timecourse (full Λ): `python pipelines/rm_timecourse_ctmc2.py examples/ctmc_params_general.json 1e84000`

- Dominance ridge (μ‑ratio at P1=0.5): `python pipelines/ridge_from_params.py 0.02 0.015`

 

**Licensing inside the bundle**

- **Code**: MIT (see `CODE_LICENSE_MIT.txt`)

- **Text & figures**: CC BY 4.0 (see `DOCS_LICENSE_CC_BY_4_0.txt`)

 

**Reproducibility notes**

- File inventory + hashes: `TMD_Zenodo_file_inventory.(md|csv)`

  • Exact figure captions: `figure_captions.md`

 

Maldonado, R. (2025). Mutation by Natural Dominance (TMD): a testable framework for evolution and the origin of life — software & data (v0.8) [Software]. Zenodo. https://doi.org/10.5281/zenodo.17335715

Notes (English)

Plain-language summary:

This project introduces *Mutation by Natural Dominance (TMD)* — a new scientific framework that helps explain **why evolution often follows the easiest path**.

When living things adapt, there are many possible genetic routes to the same outcome. Some routes happen more often because the chemistry of DNA makes certain mutations easier, or because parts of the genome are more “exposed” when cells copy their DNA. TMD captures this idea in one simple rule:

> The path that happens most easily is the one most likely to appear first.

TMD combines three measurable factors:
- **μ (mutation rate)** – how often a DNA change happens,  
- **A (accessibility)** – how open or exposed that part of the genome is,  
- **F (fixation probability)** – how likely that change is to spread through a population.

Together these form the **Mutation Dominance Index (MDI = μ × A × F)** — a score that predicts which adaptive path will “win the race” when several are possible.

The record you’re viewing includes open-source software, data, and ready-to-use figures for testing this framework in the lab or classroom. It’s written in Python and designed for reproducibility and transparency.

If the preregistered experiments confirm these predictions, TMD could help scientists better understand how new traits evolve, how antibiotic resistance appears, and how life’s earliest molecules began to change and diversify.

Files

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Additional details

Additional titles

Alternative title (English)
Mutation by Natural Dominance (TMD): execution kit (v0.8)

Software

Programming language
Python
Development Status
Active