FAU Receives NSF Grant to Explore Trait Evolution Across Species

Trait Evolution, Evolution, Machine Learning, Engineering, Computer Science, Biology, National Science Foundation

By gisele galoustian | 9/23/2021

Long after Charles Darwin’s theory of evolution and natural selection, trait evolution and the Earth’s astonishing biodiversity continue to perplex biologists. The ability to understand what shapes trait evolution across species remains complicated because tools currently available to conduct experiments that rely on accurately making assumptions about evolutionary history are lacking.

To overcome this obstacle, researchers from Florida Atlantic University’s College of Engineering and Computer Science have received a three-year, $596,571 grant from the National Science Foundation to create new paths to test evolutionary hypotheses using novel statistical and machine learning tools.

“The tools we have developed will improve the way classical statistical approaches are conducted and will provide evolutionary biologists with a method to help them answer an array of questions related to evolution across species,” said Raquel Assis, Ph.D., principal investigator, associate professor, Department of Electrical Engineering and Computer Science and a fellow of FAU’s Institute for Human Health and Disease Intervention (I-HEALTH), who is working on this project with co-PI Michael DeGiorgio, Ph.D., associate professor in the Department of Electrical Engineering and Computer Science.

Assis and DeGiorgio previously developed the first machine learning algorithm for classifying evolutionary outcomes and predicting parameters of duplicate genes from expression data. Their current project involves statistical and supervised machine learning approaches to vigorously and accurately predict general and specific evolutionary mechanisms that also will be applicable to various genomic and transcriptomic data for evolutionary discovery.

“Professors Assis and DeGiorgio are at the forefront of elucidating trait evolution among species and all of the tools and datasets generated by this project will be available to the scientific community at large,” said Stella Batalama, Ph.D., dean, College of Engineering and Computer Science. “Moreover, the project will involve underrepresented groups in science and engineering through recruitment of female Hispanic high school and undergraduate students, and also will provide hands-on courses in evolutionary genomics and bioinformatics for local senior citizens and for Native American communities across the country.”