Lars Arvestad

This paper introduces dnctree, a divide-and-conquer method for phylogeny inference that reduces time complexity from cubic to quadratic, enabling scalability for large datasets.

The paper assembles the Norway spruce mitogenome using machine learning and long reads, revealing heterogeneous recombination dynamics and active small repeats in plant mitogenomes.

The paper improves structural variation detection by introducing a more accurate null hypothesis, reducing false positives and correcting a bias in variant calling.

The paper improves genome scaffolding by addressing PE-contamination in mate-pair libraries using an ILP-based approach in the BESST scaffolder, showing significant quality improvements.