Evomorph: Evolutionary morphometrics tool using Aegla singularis data
Abstract
Macroevolutionary processes are difficult to measure as evidence in living organism. Computational simulation is an acceptable way to evaluate and understand those processes over major scales [1,2]. You can simulate evolution in a population varying different parameters (effective population size, phenotypic variance, and heritability), under different types of evolutionary mechanisms (drift, selection, etc.). In this work, we present an informatics tool to study evolutionary aspects using shape data of any species.