Our main research interests are concerned with the broad field of plant evolution and phylogenetics.
We use comparative, bioinformatics approaches to gain insights into the fascinating evolutionary dynamics of plant genomes.
In this process, we develop novel computational tools, based on machine learning, reinforcement learning, and advanced probabilistic evolutionary models.
These allow us to gain novel biological insights from various kinds of data.
Current projects in the lab include:
Studying the consequences of whole genome duplications on patterns of lineage diversification, biogeography, and the effect of polyploidy on evolutionary patterns at the molecular and genomic levels.
We are developing computational tools and apply them to genomics data to enhance our understanding regarding the relationship between the genotype and the phenotype.
By applying these methods we aim to understand the factors that influence the rate of genome evolution.
We also devise new methodologies, based on artificial intelligence, to facilitate more accurate phylogenetic analyses.
Using a combination of computational tools with large scale genomics data we hope to gain novel insights into the evolutionary consequences of plant domestication and the evolutionary selection forces that shaped their genomes.
By identifying unique patterns of selection acting on certain genes, we aim to reveal common genomics characteristics of plant crops that are important for human consumption.