Nathan Kolbow

This paper extends the SNaQ method to infer complex semi-directed phylogenetic networks, showing improved accuracy and scalability for reconstructing reticulate evolutionary histories.

SNaQ.jl improves scalability for phylogenetic network inference by enhancing computational efficiency without altering method accuracy.

This paper introduces Qsin, a sparse learning method that reduces the size of concordance factors tables for phylogenetic network inference while maintaining accuracy and reducing computational time.

This paper introduces InPhyNet, a method for scalable phylogenetic network inference that merges level-1 networks to achieve linear scalability and high accuracy.