N. Tahiri

This paper introduces a method to infer multiple alternative consensus trees and supertrees using k-means clustering and Robinson and Foulds distance to capture diverse evolutionary patterns in phylogenetic trees.

This paper introduces a deep learning method to cluster phylogenetic trees, enabling the identification of homogeneous or heterogeneous groups of trees and improving efficiency for large datasets.