TriLoNet

TriLoNet constructs rooted level-1 phylogenetic networks from aligned DNA sequence data to represent reticulate evolutionary processes such as hybridization and recombination.

Key Features:

• Level-1 Network Construction: Produces rooted level-1 networks that represent one reticulate event per tree branch to depict hybridization and recombination.
• Bottom-Up Approach: Employs a bottom-up algorithm akin to Neighbor-Joining that incrementally combines smaller level-1 networks on three taxa to form larger networks.
• Comparison with Lev1athan: In comparative simulations, yields more accurate representations of reticulate events and avoids the overestimation observed with Lev1athan.
• Input and Implementation: Implemented in Java and operates directly on aligned DNA sequence data, including data involving recombination from simulated and real datasets.

Scientific Applications:

• Evolutionary biology and phylogenetics: Reconstruction of reticulate evolutionary histories involving hybridization and recombination.
• Genetics and bioinformatics: Analysis of sequence datasets to detect and represent recombination and other reticulate processes in species relationships.

Methodology:

Implemented in Java; constructs rooted level-1 networks from aligned DNA sequences using a bottom-up Neighbor-Joining–like strategy that combines level-1 networks on three taxa incrementally.