Translational Bioinformatics Workshop
Biobanks in the Precision Medicine Era
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.
We are hosting a TBI workshop at PSB 2020, which is co-sponsored by the Asia-Pacific Translational Bioinformatics Conference (TBC). The theme is “Biobanks in the Precision Medicine Era”. Due to the increasing number of growing biobanks, and the opportunities for bioinformatics to drive discovery and implementation science, this topic is ripe for discussion at PSB 2020. We will have speakers from academia and industry discuss the strengths, challenges, and opportunities for using biobanks in precision medicine.
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.
Marylyn Ritchie, University of Pennsylvania, Why use biobanks for precision medicine
Matt Nelson, GlaxoSmithKline, How pharma uses biobanks for precision medicine
Joanna Mountain, 23andme, The power of recreational genomics for precision medicine
Ju Han Kim, Seoul National Univ. College of Medicine, Towards precision pharmacotherapy from rare and common variants in your personal genome
Jason Moore, University of Pennsylvania, Harnessing AI and Machine Learning in biobanks - the future and the now
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 Ha 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.
Marylyn Ritchie, PhD
Associate Director of Bioinformatics, Institute for Biomedical Informatics
University of Pennsylvania
Marylyn D. Ritchie, PhD is a faculty member in Genetics, Director of the Center for Translational Bioinformatics, Associate Director for Bioinformatics in the Institute for Biomedical Informatics at the University of Pennsylvania School of Medicine. Dr. Ritchie is a statistical and computational geneticist with a focus on understanding genetic architecture of complex human disease. She has expertise in developing novel bioinformatics tools for complex analysis of big data in genetics, genomics, and clinical databases, in particular in the area of Pharmacogenomics. Dr. Ritchie has extensive experience in all aspects of genetic epidemiology and translational bioinformatics as it relates to human genomics. She also has extensive expertise in dealing with big data and complex analysis including GWAS, next-generation sequencing, data integration of meta-dimensional omics data, leading large collaborative efforts, using electronic health records and genomics data for research, Phenome-wide Association Studies (PheWAS), and development of data visualization approaches.