Identifying Toxicity Pathways for High-Throughput Screening
Christopher J. Portier
Office of Risk Assessment Research
National Institute of Environmental Health Sciences
Biomedical research has resulted in vast amounts of results and data
usually stored on different databases. Using such data, we have
developed a framework for generating hypotheses relevant to the
understanding of complex diseases (like cancer), viewed as an
interplay between genetic and environmental factors. The links between
the different complex diseases and environmental factors were derived
using a novel algorithm (Structurally Enhanced Pathway Enrichment
Analysis, SEPEA) that finds significantly enriched networks of genes
or proteins. In the first part of the talk, I will elaborate on the
description and evaluation of SEPEA. Then I will describe the network
of diseases and environmental factors that resulted from the
application of SEPEA to the integrated data obtained from a
gene/disease polymorphism database, a gene/environmental factor
database and a biochemical pathway database. Here I will specifically
talk about the overall validation of the network, validation of the
metabolic diseases sub-cluster of this network and insights and
hypothesis that we obtain by an evaluation of the cancer sub-cluster.
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