Samuel V. Scarpino

University of Texas at Austin
1 University Station, #C0930
Austin, TX 78712

Phone : (512)471-3760
Email : scarpino[at]utexas.edu

Research Interests

Please see my page on the Kirkpatrick Lab website for additional information and a current CV.

My research questions fall under the headings of molecular and theoretical population genetics and mathematical epidemiology. Currently, I am focused on three lines of investigation:

Sex Chromosome Evolution in Xiphophorus: The pattern of genetic variation in a population contains information on the stochastic, demographic, and selective forces that have shaped its history. Unlocking this information requires the joint application of population genetic theory and data. Using fish in the genus Xiphophorus, I am investigating the population genetics of a potent, sex-linked oncogene Xmrk and its autosomal repressor Diff. Our broad goal is to better understand the factors driving rapid sex chromosome evolution in Xiphophorus maculatus and the evolutionary interaction between the oncogene Xmrk and its repressor across the genus. This research is done in collaboration with Mark, Patrick Hunt (a talented undergraduate at UT), Manfred Schartl at Biozenrum Universitaet Wuerzburg, and Francisco Garcia de Leon at CIBNOR in La Paz, MX.

Polyploidy and Diversification in Angiosperms: Why are polyploids so abundant in many flowering plant groups? What evolutionary processes are most important for explaining their prevalence? These questions have been central to the study of plant evolution for the last 50 years. Using a forward time model, stochastic simulations, and Approximate Bayesian Computation (ABC), I estimated diversification and polyploidization rates for 60 angiosperm genera. Our results suggest that diploids and polyploids do not diversify at significantly different rates, but that diploids may achieve a speciation advantage through their tetraploid ancestors. We also found a proportionally higher increase in diploid speciation rates due to random extinction as compared to congeneric polyploids. This research was done in collaboration with Lauren Meyers and Don Levin at UT Austin.

Optimizing Provider Recruitment for Public Health Surveillance Networks: State public health authorities in the US are mandated by the Centers for Disease Control to gather weekly reports on influenza activity from primary health care providers. These data inform public health decisions and are critical during the emergence of new influenza strains. However, most decisions on where to collect data are made using loose or ad hoc guidelines. To address this issue, we developed a computational algorithm for optimizing provider recruitment into these influenza surveillance networks. The networks designed using our method are more efficient and contain higher quality information than existing networks. Results form our research were used by the Department of State Health Services in Texas to evaluate their existing influenza surveillance network. This work was done in collaboration with Lauren Meyers at UT Austin and Ned Dimitrov at the Naval Postgraduate School in Monterey CA.

I am also broadly interested in statistical modeling and as a result have worked on a number of exciting projects including: heritable, epigenetic modifications in rats, models of spatiotemporal variation in phenology, and estimating epidemiological parameters early in an outbreak (2009 H1N1). I plan to complete my dissertation research in spring 2013 and hope to begin postdoctoral work in late-summer or early fall 2013.