Statistical Training to Enhance the Excellence of Research (STEER) in Biomedical Sciences

University Of California-Irvine, Irvine CA

Investigators

Abstract

Summary Large-scale biological studies along with routine use of digital sensors and mobile devices to collect medical data have created a data deluge, imposing new challenges on scientists and practitioners to process and analyze a large amount of data for information extraction, discovery, and decision making. Tackling these emerging challenges requires interdisciplinary teams of scientists with complementary domain knowledge and analytical skills, who can work together effectively toward the common goal of understanding complex biological phenomena and improving treatment effectiveness. To develop such a framework for sustainable support of collaborative environments at the intersection of biomedical sciences and biostatistics, we propose to create an integrative, interdisciplinary, and interactive training program called Statistical Training to Enhance the Excellence of Research (STEER) in Biomedical Sciences. At its core, STEER provides PhD students with the required training on statistical thinking for biomedical data analysis. We will also prepare our trainees with the required skills to handle big data problems and the associated computational challenges, given that the emerging biomedical studies have become increasingly data-intensive. Additionally, we will introduce trainees to state- of-the-art statistical machine learning techniques and their role in biomedical research. Our program's overall goal is to teach students the underlying principles of statistical analysis so they can solve real-world biomedical problems. STEER will foster a stimulating environment for training and mentoring the next generation of biomedical scientists with proper exposure to modern developments in biostatistics, and biostatisticians with expertise in solving complex and data-intensive problems for fundamental research in biomedical sciences. To this end, our research training program's main objectives are as follows: Obj 1: Use the science of team science to create a stimulating collaborative environment at the interface of biomedical sciences and biostatistics; Obj 2: Develop an interdisciplinary education framework to cultivate an exceptional learning environment for training a new generation of scientists with a deep understanding of modern biostatistical techniques and complex biomedical systems; Obj 3: Create a collaborative research framework where our trainees learn to develop innovative data analysis methods that are fundamentally sound, methodologically robust, and computationally feasible for investigating biomedical problems; Obj 4: Provide professional development training and organize career planning activities to prepare our students for a variety of academic and nonacademic career options, while ensuring a high level of PhD completion rate and appropriate time to degree.