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2025
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| Online Access: | https://doi.org/10.5281/zenodo.15209228 |
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| _version_ | 1866901881215778816 |
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| author | Reza Hashemi |
| author_facet | Reza Hashemi |
| contents | <p>This study presents a computational simulation with 100,000 runs to model DNA evolution of two plasmids—PhiC31 (3895 bp) and pCMV-LacZ-BbsI (4968 bp), totaling 8863 bp—in enucleated oocytes, nucleated oocytes, cytoplasts, liposomes, and isolated mitochondria under baseline and high-stress conditions. Using an enhanced nonlinear model, we simulated mutation rates, incorporating oxidative stress, ion dynamics, enzyme activity, mitochondrial effects, large-scale mutations, and noise. Results validated predictions from Hashemi [1] with differences <5%, showing enucleated oocytes with the highest mutation rates (0.087–1.97) versus nucleated oocytes (0.0032–0.139). Novel statistical analyses—sensitivity, correlation, two-way ANOVA, Tukey HSD, and multivariate regression (R² = 0.87)—revealed oxidative stress as a key driver of mutations. Comparisons with Sánchez et al. [2] and Gurdon et al. [3] provided biological context, confirming the role of reactive oxygen species (ROS) and cytoplasmic dynamics. Evolutionary insights suggest that high mutation rates in enucleated systems mirror prebiotic protocells, driving early genetic diversity, while nuclear repair stabilized eukaryotic genomes. This framework, supported by open-source Python code, advances computational biology and informs synthetic biology and origins-of-life research.Although these results are derived from simulations, they are highly precise and statistically robust, providing strong computational support for the Matter World Hypothesis.All findings in this study are derived from advanced estimated calculation simulations and thus require empirical validation before drawing definitive conclusions.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15209228 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Modeling DNA Evolution in Nucleus-Free and Nucleated Systems Using a 100,000-Run Simulation with Advanced Statistical Analyses(Estimated Calculation Simulation ) Reza Hashemi Computational Biology, DNA Evolution, Mutation Rates, Statistical Modeling, Evolutionary Insights, Oxidative Stress <p>This study presents a computational simulation with 100,000 runs to model DNA evolution of two plasmids—PhiC31 (3895 bp) and pCMV-LacZ-BbsI (4968 bp), totaling 8863 bp—in enucleated oocytes, nucleated oocytes, cytoplasts, liposomes, and isolated mitochondria under baseline and high-stress conditions. Using an enhanced nonlinear model, we simulated mutation rates, incorporating oxidative stress, ion dynamics, enzyme activity, mitochondrial effects, large-scale mutations, and noise. Results validated predictions from Hashemi [1] with differences <5%, showing enucleated oocytes with the highest mutation rates (0.087–1.97) versus nucleated oocytes (0.0032–0.139). Novel statistical analyses—sensitivity, correlation, two-way ANOVA, Tukey HSD, and multivariate regression (R² = 0.87)—revealed oxidative stress as a key driver of mutations. Comparisons with Sánchez et al. [2] and Gurdon et al. [3] provided biological context, confirming the role of reactive oxygen species (ROS) and cytoplasmic dynamics. Evolutionary insights suggest that high mutation rates in enucleated systems mirror prebiotic protocells, driving early genetic diversity, while nuclear repair stabilized eukaryotic genomes. This framework, supported by open-source Python code, advances computational biology and informs synthetic biology and origins-of-life research.Although these results are derived from simulations, they are highly precise and statistically robust, providing strong computational support for the Matter World Hypothesis.All findings in this study are derived from advanced estimated calculation simulations and thus require empirical validation before drawing definitive conclusions.</p> |
| title | Modeling DNA Evolution in Nucleus-Free and Nucleated Systems Using a 100,000-Run Simulation with Advanced Statistical Analyses(Estimated Calculation Simulation ) |
| topic | Computational Biology, DNA Evolution, Mutation Rates, Statistical Modeling, Evolutionary Insights, Oxidative Stress |
| url | https://doi.org/10.5281/zenodo.15209228 |