The Saba Lab is focused on applying state-of-the-art statistical methodology to the systems-level analysis of the high throughput data including genetic, genomic, and proteomic studies of complex traits. Our goal is to use the data to uncover the sequence of events that starts with DNA and ends in disease. When we know the sequence of events and all the players, we can design better drugs that can effectively treat the disease and limit the side effects. We use the breadth of data available to predict the sequences of events, so a clinician or researcher can design a better experiment that has a higher probability of success and ultimately speed up the drug development process.
My research interests focus on developing and implementing systems genetics statistical models to complex traits. Currently in the lab we are working on several different projects:
Most of my research has been studying genetic predisposition to alcohol dependence in rodent models, specifically in recombinant inbred panels of mice and rats. Much of the data produced and analysis results are available on the PhenoGen website as simple downloads or as interactive graphics.
Pathway analysis in proteomics analysis of protein modifications
Human gene association studies
|Kylie Harrall, MS|
Professional Research Assistant
Kylie double majored in Biology and Chemistry at the University of Missouri – Kansas City, and spent the following 5 years researching and developing veterinary vaccines for Boehringer Ingelheim Vetmedica and Virginia Tech University. With the desire to learn more about data analysis, Kylie returned to graduate school at the University of Colorado – Denver and completed her MS in Biostatistics. In the Saba lab, she spends her time working with high-throughput omics datasets; this work includes the integration and interpretation of RNA-Seq and microarray data, and the development and exploration of new techniques for increasing the interpretability of omics data.
|Ryan Lusk, BS|
Ryan graduated from the University of Minnesota – Duluth with a BS in Biochemistry and Molecular Biology. As an undergraduate, his research included supercritical fluid chromatography method development, biophysical characterization of intrinsically disordered proteins, and the development of techniques to examine light fluxes in lotic systems. Ryan entered the Pharmaceutical Sciences PhD program at the University of Colorado – Denver in 2015. In graduate school, Ryan discovered a passion for biostatistics, and his dissertation work seeks to combine this with his knowledge of living systems to interpret large, clinically relevant data sets in order to help answer today’s complex biomedical sciences questions.
|Harry Smith, BS|
Harry earned his Bachelor’s of Science in biology from the University of Colorado in Colorado Springs, and is currently pursing his Master’s of Public Health from the Colorado School of Public Health on the Anshutz Medical Campus. His Master’s concentration is Applied Biostatistics and BioInformatics. His research interests include genetic association studies using systems genetics, as well as machine learning in the context of health and health outcomes data. Recently, he joined the Saba lab in the Skaggs School of Pharmacy and Pharmaceutical Sciences first as an intern followed by being hired as a student employee. He is investigating the genetic influences on metabolic activities in brown adipose tissue (BAT) by gene co-expression networks associated with interesting metabolic phenotypes.
|Lauren Vanderlinden, MS|
Senior Professional Research Assistant
Lauren earned her bachelor’s degree in chemistry and mathematics from CU Boulder and MS in biostatistics from UC Denver. Previous to working at the School of Pharmacy, Lauren was a professional research assistant at the School of Medicine’s Proteomics Core and specialized in mass spectrometry. Her current research interests include applying statistical approaches to integrate a variety of high-throughput data and physiological trait data. Statistically determining both genetic and environmental underpinning of disease is the ultimate goal of her research.
Precision medicine is a multidisciplinary field that thrives on the collaboration of scientists with diverse sets of skills. In the Saba laboratory, we apply biostatistics, bioinformatics, statistical genetics, and pharmacogenetics techniques to uncover biological mechanisms of disease, to identify possible pharmaceutical targets, and to identify subpopulations that would benefit from particular drug therapies or prevention strategies.
Because of the multidisciplinary nature of the field that we study, we are interested in a broad range of students and postdoctoral fellows.
Please contact Dr. Saba for more information about any of the following: