Genomics

Yann C. Klimentidis, PhD, is an Associate Professor in the Department of Epidemiology and Biostatistics in the Mel and Enid Zuckerman College of Public Health at the University of Arizona. His research centers on improving our understanding of the links between genetic variation, lifestyle factors, metabolic disease, and health disparities. In the past, he has used measures of genetic admixture and genomic tests of natural selection to understand the genetic basis of population differences in disease susceptibility. His most recent work examines the use various statistical approaches for the analysis of high-dimensional genetic data for improving prediction of genetic susceptibility to type-2 diabetes. In addition, his work examines gene-by-lifestyle interactions in type-2 diabetes, as well as understanding the causal links between metabolic traits such as dyslipidemia and type-2 diabetes. Keywords: Genetics, epidemiology, Cardiometabolic disease, Physical activity

Dr. Bonnie Hurwitz is an Assistant Professor of Biosystems Engineering at the University of Arizona and BIO5 Research Institute Fellow. She has worked as a computational biologist for nearly two decades on interdisciplinary projects in both industry and academia. Her research on the human/earth microbiome incorporates large-scale –omics datasets, high-throughput computing, and big data analytics towards research questions in “One Health”. In particular, Dr. Hurwitz is interested in the relationship between the environment, microbial communities, and their hosts. Dr. Hurwitz is well-cited for her work in computational biology in diverse areas from plant genomics to viral metagenomics with over 1200 citations

Michael Hammer is a Research Scientist in the Division of Biotechnology at the University of Arizona with appointments in the Department of Neurology, Ecology and Evolutionary Biology, Bio5, the School of Anthropology, the University of Arizona Cancer Center, and the Steele Children's Research Center. Currently Dr. Hammer is interested in the use of the latest DNA sequencing technology to infer the underlying genetic architecture of neurodevelopmental diseases. Since 1991 Dr. Hammer has directed of the University of Arizona Genetics Core (UAGC), a facility that provides training and molecular biology services to University and biotechnology communities at large. After receiving his Ph.D. in Genetics at the University of California at Berkeley in 1984, he performed post-doctoral research at Princeton and Harvard. Over the past two decades, Dr. Hammer has headed a productive research lab in human evolutionary genetics, resulting in over 100 published articles documenting the African origin of human diversity, interbreeding between modern humans and archaic forms of the genus Homo, and genome diversity in the great apes. His lab and the UAGC were early adopters of next generation sequencing (NGS) technology and the application of whole genome analysis in humans, and his lab has been a key player in the Gibbon and Baboon Genome Projects, as well as a consortium that has analyzed the genomes of over 100 Great Apes (GAPE Project). In the past 3 years, Dr. Hammer's research team has succesfully employed NGS methods to identify molecular lesions causing neurodevelopmental disorders in undiagnosed children. This has led to the publication of articles identifying pathogenic variants associated with early onset epileptic encephalopathies. His lab is also currently pursuing studies to identify modifier genes that alter the expression of major genes and how they contribute to phenotypic heterogeneity in Mendelian disorders.

The Gutenkunst group studies the function and evolution of the complex molecular networks that comprise life. To do so, they integrate computational population genomics, bioinformatics, and molecular evolution. They focus on developing new computational methods to extract biological insight from genomic data and applying those methods to understand population history and natural selection.

Lingling An, PhD, conducts research in the interdisciplinary boundaries of many fields such as statistical sciences, biological and medical sciences, genomics and genetics. Her statistical group's major research interests include development and application of statistical and computational methods for analysis of high-dimensional genomic/genetic, metagenomic/ metatranscriptomic, and epigenomic data. The overlying vision is to develop rigorous, timely and useful statistical and computational methodologies to help biologists/geneticists to ask, answer, and disseminate biologically interesting information in the quest to understand the ultimate function of DNA and gene network.