Takahiro Sakamoto

This study shows that biases in rescaling forward-in-time population genetic simulations can be reduced by using a different simulation algorithm.

This paper introduces SimGEA, a simulation-based method for genotype-environment association analysis that controls false discovery rates while maintaining statistical power.

This study develops an evolutionary model showing how disruptive selection can lead to the spontaneous emergence of a sex-determining locus and sexual differentiation through gene regulatory networks.

The paper develops a theoretical method to analyze complex spatially heterogeneous population models and shows that high environmental spatial autocorrelation promotes the maintenance of locally adaptive alleles.

This study develops a multidimensional continuous space model to analyze the establishment of local adaptation, showing how mutation and migration influence adaptation rates in spatially heterogeneous environments.

This paper develops a mathematical model to analyze how mutation swamping affects genetic architecture under varying mutation rates and selection pressures, finding a threshold mutation rate range of 10^-3 to 10^-2.