Gergely J. Szöllősi

This paper improves ancestral genome reconstruction by incorporating gene-content grammar, leading to more accurate and consistent reconstructions across different methods.

The paper uses phylogenetic methods to determine the root of the Archaea, finding support for a methanogenic ancestor and a derived origin for host-associated lineages.

This paper shows that adding noise to gene content data improves machine learning predictions of bacterial phenotypes across evolutionary time, concluding the last bacterial common ancestor was anaerobic, double-membraned, and moderately thermophilic.

This study examines how gut bacteria genomes adapt to industrialization, finding convergent genomic responses in stress response, cell envelope remodeling, and central metabolism across different populations.

This study resolves the phylogenetic position of Njordarchaeales and Panguiarchaeales, placing them as a new class Njordarchaeia within Asgard archaea and identifying Panguiarchaeum as a metabolically reduced, potentially symbiotic lineage.

AleRax estimates gene and species trees together using a probabilistic model of gene duplication, transfer, and loss, achieving higher speed and robustness than existing methods.

SpeciesRax infers species trees from gene family trees, accounting for duplication, transfer, and loss, and is accurate and faster than existing methods.

The paper develops a method to estimate cell turnover and mutation rates from bulk sequencing data, finding both are elevated in a hepatocellular carcinoma sample.

The paper introduces EDCluster, a scalable method for empirical distribution mixture models that reduces long branch attraction artifacts and improves performance over existing models.

GeneRax infers gene trees using a species tree-aware maximum likelihood approach, outperforming existing tools in accuracy and speed on both simulated and empirical data.

Zombi simulates species, genomes, and sequences evolution, including extinct lineages and speciation/extinction rate variations.

The paper quantifies GC-biased gene conversion in great ape genomes using a new polymorphism-aware model that accounts for allelic selection and demography.

MaxTiC ranks a species tree by maximizing time consistency with lateral gene transfer constraints, achieving accurate results on simulated and biological datasets.