Seminar Series - Jong Cheol Jeong, PhD -- The Questions and Answers for Biomedical Data Science
Tuesday, May 9, 2017
014 CTW Building
The Questions and Answers for Biomedical Data Science
Jong Cheol Jeong, PhD
Beth Israel Deaconess Medical Center
Harvard Medical School
Computational Biology and Bioinformatics are multidisciplinary fields that apply both computational power and complex methods for the retrieval, integration, and analysis of various types and scales of data from different fields of studies. As technology and biomedical research continues to evolve and progress, the computational biology and bioinformatics community has discovered numerous challenges and problems pertaining to the advancement of the field. Therefore, this talk will introduce some of the useful technologies in data driven biomedical studies while answering three key questions with practical studies: i) how to use the current biomedical techniques in relevant clinical and research studies, for example, the evolution of epithelial and stromal network connectivity during carcinogenesis. ii) problem solving when current technologies are not suitable, for example, a machine learning-based high throughput method to detect interface residues in protein-protein interaction will be introduced, and iii) how to explore data produced by various technologies; gene ontology-based new semantic similarity, so called biological and statistical mean score (BSM) will be discussed. As increasing demand for providing fully functional applications as well as developing new methods and algorithms in bioinformatics, this talk will also cover method deployment that introduces existing services in web-based, high performance, and cloud computing environments.
Jong Cheol Jeong is a research fellow in Beth Israel Deaconess Medical Center, Harvard Medical School and earned his PhD degree in Bioengineering from the University of Kansas, Lawrence, KS in 2013. His method in identifying interface residues in protein-protein interaction has been cited more than 100 times and been referred to as fundamental criteria for imbalanced data analysis. He received the best research paper award from Korea Fuzzy Logic and Intelligent System 2001 and was awarded the Wallace S. Strobel Scholarship from University of Kansas in 2008. He was selected as one of the five Hub Heros of U.S.A in 2014. He is currently leading two open source projects: ST-analyzer - an automated analysis tool for molecular dynamics simulation trajectory and ImagePath - an image annotation tool for microscopic tissue images. His research interests are in designing and implementing methods for analyzing biomedical data by integrating deep profiling features derived from Big data and Machine learning methods.