Translational Bioinformatics Workshop
Translational bioinformatics (TBI) is a multi-disciplinary and rapidly emerging field of biomedical data sciences and informatics that includes the development of technologies that efficiently translate basic molecular, genetic, cellular, and clinical data into clinical products or health implications. TBI is a relatively young discipline that spans a wide spectrum from big data to comprehensive analytics to diagnostics and therapeutics. TBI involves applying novel methods to the storage, analysis, and interpretation of a massive volume of ‘omics and clinical data, and it bridges the gap between bench research and real-world applications to human health. Many health-related topics are increasingly falling within the scope of TBI, including rare and complex human disease, cancer, biomarkers, pharmacogenomics, drug repositioning, and clinical decision support systems.
TBI in precision medicine attempts to determine individual solutions based on the genomic, environmental, and clinical profiles of each individual, providing an opportunity to incorporate individual genomic data into patient care. While a plethora of genomic signatures have successfully demonstrated their predictive power, they are merely statistically-significant differences between dichotomized phenotypes that are in fact severely heterogeneous. Despite many translational barriers, connecting the molecular world to the clinical world and vice versa will undoubtedly benefit human health in the near future.
TBC began in 2011, as a venue for highlighting the multi-disciplinary nature of the research field and to provide an opportunity to bring together translational bioinformatics researchers. TBC has always put an emphasis on promoting translational bioinformatics research activities initiated in the Asia-Pacific region, where the meetings have been held in Korea, China, and Japan. We have also hosted one event in Los Angeles, CA. For TBC 2020, we would like to bring the event to the Pacific, and host a workshop in conjunction with PSB, rather than an independent conference. Translational bioinformatics is a fast-moving field and we believe that bringing the TBC community together with the biocomputing community at PSB will be mutually beneficial.
Jason Moore, PhD
Director, Institute for Biomedical Informatics
University of Pennsylvania
Dr. Moore is a translational bioinformatics scientist and human geneticist whose research focuses on the development and application of artificial intelligence and machine learning methods for modeling complex patterns in biomedical big data. One central focus of his is using informatics methods to identify combinations of DNA-sequence variations and environmental factors that predict human health and complex disease. For example, he developed the multifactor dimensionality reduction (MDR) machine-learning method for detecting and characterizing combinations of attributes or independent variables that interact to influence a dependent or class variable. He then applied MDR to improve how we understand the interplay of multiple genetic polymorphisms of in . He is the founding editor-in-chief of the journal . He has published more than 450 peer reviewed articles, book chapters and editorials. His translational bioinformatics research program has been continuously funded by multiple grants from the National Institutes of Health for more than 15 years.
Ju Han Kim, MD, PhD, SM
Professor and Founding Chair of the Division of Biomedical Informatics
Seoul National Univ. College of Medicine
Ju Han Kim, MD, PhD is Professor and Founding Chair of the Division of Biomedical Informatics, Seoul National Univ. College of Medicine, in South Korea. Dr. Kim’s carrier has been focused on the state-of-the-art informatics technology and its impact on and utility of biomedical sciences and clinical practice. With his expertise in pattern analysis and machine learning technologies as well as his understanding in biomedical and clinical sciences, Dr. Kim is currently developing an integrated personal genome interpretation system, which aims to integrate rare and common human genome variants with clinical phenotypes and evolutionary constraints in pursuit of fundamental understanding of the genomic landscape of human health and molecular pathophysiology.
Dokyoon Kim, PhD
Assistant Professor of Informatics
University of Pennsylvania
Dr. Dokyoon Kim is an Assistant Professor of Informatics at the Department of Biostatistics, Epidemiology and Informatics within the Perelman School of Medicine at the University of Pennsylvania. He is also a senior faculty at Penn Institute for Biomedical Informatics. Dr. Kim has considerable biomedical informatics expertise in methods development for data integration using machine learning and other analytic challenges. His research entails the development and application of data integration approach to improve the ability to diagnose, treat, and prevent complex diseases. His primary focus lies in integrating multi-omics data, biological knowledge, and imaging data to better translate genomic and biomedical data from electronic health records (EHR) into clinical products. His projects have been both theoretical and applied, and they include developing novel data integration methods that combine multi-omics data and biological knowledge, predicting clinical outcomes based on interactions between multi-omic features, integrating multi-modal neuroimaging and multi-omics data, and identifying gene-gene (GxG) and gene-by-environment (GxE) interactions in several phenotypes/diseases.