|Michael Bereman, Ph.D., is an assistant professor in the Department of Biological Sciences and a member of the Center for Human Health and the Environment (CHHE) at North Carolina State University in Raleigh, NC. The central focus of his research is to develop innovative, quantitative methodologies to investigate the interplay between environment and genetic factors with respect to human health and disease. The assessment of a vast number of environmental exposures on disease risk remains a critical – yet unfulfilled challenge. His efforts focus on the continued improvements in technology with applications in two key areas: 1) Development of assays to quantify the degree of overall exposure in biological fluids using existing and novel protein modifications; and 2) The elucidation of the impact of various environmental exposures on the etiology of diseases using both human specimens and animal models. Prior to joining NCSU, he held a post-doctoral position in the Department of Genome Sciences at the University of Washington where he focused on instrumentation development, targeted assays for determining protein metabolism, and quality control in proteomics.
Statistical Process Control for Accessing Data Quality Throughout an LC MS/MS ExperimentStatistical process control (SPC) is a robust set of tools that aids in the visualization, detection, and identification of assignable causes of variation in any process that creates products, services, or information. Its power as a quality control procedure lies in its primary focus on early detection of a process performing outside defined thresholds and the subsequent determination of the cause of that variation. In this presentation the method of statistical process control is discussed, how it can be used to monitor data quality in proteomics via LC MS/MS, and its implementation into Skyline as an application.