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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