Evolutionary modeling is the construction and analysis of computational or mathematical models that simulate how biological systems change over time under evolutionary forces such as mutation, selection, drift, and migration. By representing populations, traits, or genetic sequences and applying rules derived from e…
Evolutionary modeling is the construction and analysis of computational or mathematical models that simulate how biological systems change over time under evolutionary forces such as mutation, selection, drift, and migration. By representing populations, traits, or genetic sequences and applying rules derived from evolutionary theory, researchers use these models to test hypotheses about how species, populations, and ecosystems develop, and to explore questions in genetics, ecology, epidemiology, and medicine that are difficult to address through observation alone. Evolutionary modeling also encompasses computational techniques inspired by natural selection, including genetic algorithms and evolutionary computation, which apply principles of variation and selection to optimisation and search problems. Model Based Research focuses on this broader enterprise of representing complex systems through formal models and simulations across scientific disciplines. While the journal's published work spans applied modelling and computational methods, evolutionary modeling specifically draws on iterative, selection-based approaches to understanding change in living and engineered systems. This page collects peer-reviewed, open-access research relevant to evolutionary modeling, situating it within the journal's emphasis on model-driven analysis and simulation as tools for scientific inquiry.
1 peer-reviewed article, ranked by relevance. Each links to its DOI.
The 1 article above has been cited 2 times in the scholarly literature. Citation data via OpenAlex and Crossref, updated Jun 2026.
A sample of recent works citing this journal's research on Evolutionary Modeling, linking to each citing work.