Gennady Margolin
About Gennady Margolin
Gennady Margolin is a Bioinformatics Scientist with extensive experience in investigating epigenetic biomarkers for cancer detection. He has worked at the National Institutes of Health since 2013 and has a PhD from the Weizmann Institute of Science.
Work at National Institutes of Health
Gennady Margolin has been employed at the National Institutes of Health (NIH) since 2013, serving as a Bioinformatics Scientist. His role involves investigating candidate pan-cancer epigenetic biomarker loci that are suitable for liquid biopsy. He collaborates with various genomic data repositories, including The Cancer Genome Atlas (TCGA), Genomic Data Commons (GDC), and Broad Firehose. Prior to his current position, he worked at NIH as a Research Fellow from 2008 to 2013, contributing to projects focused on bioinformatics and cancer research.
Education and Expertise
Gennady Margolin earned his Doctor of Philosophy (PhD) from the Weizmann Institute of Science. His educational background provides a strong foundation in bioinformatics, particularly in statistical data analysis. Margolin specializes in developing multi-locus epigenetic biomarker panels aimed at tumor detection and type classification. His expertise extends to characterizing gene expression and DNA methylation in both healthy and cancerous samples.
Background
Before joining the National Institutes of Health, Gennady Margolin worked as a Research Associate at the University of Notre Dame from 2003 to 2008. During this five-year tenure, he focused on research that contributed to the understanding of cancer biology and bioinformatics. His experience at both institutions has shaped his research interests and methodologies in the field of bioinformatics.
Research Focus and Projects
Gennady Margolin's research primarily focuses on the investigation of epigenetic biomarkers for cancer. He is involved in developing panels that can detect tumors and classify their types based on multi-locus epigenetic data. His work includes analyzing genomic data from various repositories to identify potential biomarkers that can be utilized in liquid biopsy, thereby advancing the field of cancer diagnostics.