Characterization of Genetic and Epigenetic Variation Data in Tumors
The genetic variation found among individuals results in patterns of polymorphisms passed down through generations. This evolutionary variation typically holds true for individuals, samples from the same population or subpopulation, and cells taken from a single tumor.
In this webinar, Dr. Paul Marjoram will explore how statistical analysis of polymorphism data can be used to examine a number of issues relating to cancer, including:
- how patterns of polymorphism induced by somatic mutation in tumors can be best understood and then used to differentiate tumor types or sub-types.
- how epigenetic polymorphism, or lack thereof, can be exploited to reveal a single gene of “importance.”
- how genetic polymorphism within a single tumor can be used to address questions about the makeup of that tumor (i.e., “How many stem cells does this tumor have?”).
Using a statistical perspective, Dr. Marjoram shows how Big Data can be used to investigate the genetic and epigenetic variations underlying cancer.
Dr. Paul Marjoram is a research professor in the Biostatistics Division of the Department of Preventive Medicine at the Keck School of Medicine at the University of Southern California, Los Angeles. He has developed various mathematical and statistical machinery to address biological problems in areas such as population genetics, tumor evolution, association studies, and animal behavior.
Upcoming Events
- Precision Medicine Approach to Breast Cancer Detection and DiagnosisDecember 06, 2021Interpretable and Explainable Deep LearningDecember 15, 2021