Biostatistics/SAGE Seminars

Dr. Quan Long of the Departments of Biochemistry & Molecular Biology and of Medical Genetics at the University of Calgary, is giving the Fall 2016 SAGE/Biostatistics Seminar entitled Modeling genetic background by linear mixed models: applications on genome and gene expression data on Friday, November 18, 2016. Summary of the talk: One of the major promises of the field of genomics is the establishment of a complete genotype phenotype map; a tool with the capacity to precisely identify the genetic mechanisms responsible for a given set of symptoms presenting in a patient. Such a tool would revolutionize our ability to deliver healthcare that is customized to the individual patient (precision medicine), by enabling accurate disease detection and early intervention with the most appropriate and effective treatment for that individual. Empowered by the next-generation high-throughput sequencing technology, researchers are generating genomics data containing millions of genetic polymorphisms. In contrast, the best-funded medical genomics studies can include cohorts of only hundreds or thousands of patients. This suggests that established techniques for big-data mining may suffer from “overfitting” and more biological insights must be leveraged. In this talk, Dr. Quan Long will present how to utilize genetic background using linear mixed models to strike a good balance between overfitting and underfitting. Their application on genomes and gene expression data will be demonstrated.

Location:

Mathematical Sciences 427

Speaker:

Dr. Quan Long, Departments of Biochemistry & Molecular Biology and of Medical Genetics, University of Calgary

More information at http://www.ucalgary.ca/events/calendar/biostatisticssage-seminars