Remember domain, kingdom, phylum, class, order, family, genus, species and Darwin's tree of life metaphor we learned about in high school biology? That way of describing living-things lineages is just science's best guess about how genes have mutated and split over time to change things into what they are today. It's not uncommon for living things to be reclassified into another genus as science gets better at identifying protein and gene changes; for example, there have been recent changes in taxonomy of different kinds of bacteria, plants and coral. What if you could make a better model of evolutionary change that, while maybe not 100 percent accurate - considering complex organisms have been evolving for billions of years - could give you a clearer picture than ever before? Kristen Naegle, associate professor ofbiomedical engineeringandcomputer scienceat the University of VirginiaSchool of Engineeringand resident faculty member of UVA'sCenter for Public Health Genomics, and her former Ph.D. student, Roman Sloutsky, now a post-doctoral researcher at the University of Massachusetts Amherst, have done just that. Their work shows how to build models reconstructing evolutionary change much more accurately than ever before, which holds promise for breakthroughs in understanding how diseases work in the human body. Their paper, “ASPEN, a methodology for reconstructing protein evolution with improved accuracy using ensemble models,â€was published Thursday, Oct. 17, in the journal eLife. ASPEN stands for “Accuracy through Subsampling of Protein EvolutioN.†Their research highlights UVA's strengths in biomedical data sciences.