Statistics and Data Science Seminar
Jie Yang
University of Illinois at Chicago
Biomedical Big Data and Permanental Classification Approach
Abstract: The explosion in the availability of biomedical data is
creating both great opportunities and challenges for collaborative
research among clinicians, genomics and proteomics scientists,
molecular biologists, and statisticians. On one hand, electronic
medical records and genomic data of a large cohort of individuals
are assembled and become available for health study researches. On
the other hand, the combined data are extremely high-dimensional
and also becoming bigger and bigger, especially the genomic part.
As one of the most critical application areas with the biomedical
big data, precision medicine refers to precisely classifying
individuals into subpopulations according to their susceptibility
to a particular disease and precisely tailoring of medical
treatments to subcategories of the disease. Achieving the goals
of precision medicine requires combining data across multiple
formats and developing novel, sophisticated statistical methods.
Our permanental classification approach recently developed
is capable of handling high-dimensional classification problems.
It provides a promising solution for biomedical high-dimensional
data, implemented using the most popular open source statistical
software, R.
Wednesday January 20, 2016 at 4:00 PM in SEO 636