Our research
focuses on understanding how genetic diversity
provides insights into the predisposition to cancer. As we
learn more about the complexity of the human genome from
programs like the HapMap and ENCODE projects, it becomes
evident that our understanding of genetic diversity is
incomplete. Structural variants,
specifically in the form of Copy Number Variants (CNVs), add
to the genomic diversity encoded in single DNA base-pair
difference, referred to as Single Nucleotide Polymorphism
(SNPs). Emerging data from a number of groups supports the
view that genomic mutations (SNPs or CNVs) are associated with
increased risk of developing specific diseases, such as early
onset Alzheimer-s and diabetes.
We develop analytical
computational approaches to extract information on the
landscape of genetic diversity as appreciated using
high-throughput genome-wide data (Affymetrix 6.0, Agilent,
NimbleGene). Currently, we are exploring a large
population-based cohort from Tyrol Austria and a U.S. Cohort
from a prostate cancer screening trial.
Concurrent research
interests include the identification of genes and pathways
which play key role in the progression of cancer. We integrate
genomic and transcriptome data to identify mechanisms driving
tumor progression. The analysis results are starting points
for validation in wet
laboratories. |