Photograph of Alison Davis Rabosky
Applications:
Behavioral Science, Bioinformatics, Biological Sciences, Ecological Research, Environmental Sciences, Genetics, Genomics
Methodologies:
Artificial Intelligence, Data Visualization, Digital Data Curation, High-Dimensional Data Analysis, Image Data Processing and Analysis, Longitudinal Data Analysis, Machine Learning, Spatio-Temporal Data Analysis, Statistical Modeling

Alison Davis Rabosky

Assistant Professor and Curator

Department of Ecology and Evolutionary Biology


Affiliation(s):

University of Michigan Museum of Zoology (UMMZ)

Our research group studies how and why an organism’s traits (“phenotypes”) evolve in natural populations. Explaining the mechanisms that generate and regulate patterns of phenotypic diversity is a major goal of evolutionary biology: why do we see rapid shifts to strikingly new and distinct character states, and how stable are these evolutionary transitions across space and time? To answer these questions, we generate and analyze high-throughput “big data” on both genomes and phenotypes across the 18,000 species of reptiles and amphibians across the globe. Then, we use the statistical tools of phylogenetic comparative analysis, geometric morphometrics of 3D anatomy generated from CT scans, and genome annotation and comparative transcriptomics to understand the integrated trait correlations that create complex phenotypes. Currently, we are using machine learning and neural networks to study the color patterns of animals vouchered into biodiversity collections and test hypotheses about the ecological causes and evolutionary consequences of phenotypic innovation. We are especially passionate about the effective and accurate visualization of large-scale multidimensional datasets, and we prioritize training in both best practices and new innovations in quantitative data display.