Our research focuses on developing and implementing computer vision tools that help us understand the evolvability of complex organisms, with particular emphasis on the role of modularity and developmental constraints in shaping multivariate evolution. The lab has several ongoing projects, with research organisms that range from marine invertebrates (bryozoans) to mammals, and it uses a wide-array of approaches, varying from genomics to machine-learning. Learn more about our projects below: 

Machine-learning-based Phenomics

Large-scale phenotyping (phenomics) is a budding discipline in evolution, ecology and paleobiology. In the BioVision Lab, we are developing and implementing cutting-edge machine-learning tools to extract high-dimensional high-throughput phenotypic and quantitative genetic data from both fossil and extant lineages. These open-access tools are available on github. Check the Software tab for more details.

We are also core developers and contributors to SlicerMorph.

SlicerMorph aims to enhance the open-source 3D Slicer platform with cutting-edge tools to assist biologists, anthropologists, and morphologists in analyzing 3D data from research imaging modalities. Our ultimate goal is to foster a collaborative community within the 3D Slicer ecosystem to facilitate seamless data exchange and promote the advancement of open science. See more here.

The Paradox of Stasis

Evolutionary biologists have long sought to understand the processes that have shaped the morphological diversity of living organisms. Studies in contemporary populations often observe strong selective episodes which, when combined with the abundant genetic variation typically observed for individual traits, should lead to substantial and rapid diversification. The fossil record, on the other hand, shows substantive evidence of stasis, defined as long periods of little to no net morphological change. Together, these contrasting observations point to a critical gap in our understanding of the evolutionary processes taking place on ecological compared to geological timescales. This critical gap, termed “the paradox of stasis”, is one of the most neglected theoretical problems in evolutionary biology. Our research on this topic uses combination of novel empirical and methodological approaches to disentangle the role of evolutionary processes and developmental constraints in shaping evolutionary change in complex morphological traits. Key aspects of the project include the use of a unique marine invertebrate model system (bryozoans) in which the shape of the adaptive landscape of phenotypic traits can be inferred directly from fossil specimens, due to the preservation of reproductive structures. 

Genotype-to-Phenotype Map

Our research in this area focuses on the opportunities brought out by the increased availability of large genomic datasets and asks questions at the intersection of genetics and evolution. How does natural selection reshape the genetic architecture of complex traits? What is the speed, and through which mechanisms are such changes achieved? To what extent does the genetic architecture of traits influence macroevolutionary diversification patterns? To answer these questions, we use both empirical and theoretical approaches, using both the skull and blood lipids of mammals as model systems to tackle such questions.