Humans are constantly exposed to complex mixtures of environmental chemicals. However, scientists are unaware of the effects of most of these chemicals on human health. Several ongoing efforts are seeking to fill this gap. For example, the EPA/NIH-funded ToxCast and Tox21 initiatives monitor the effect of chemicals on selected proteins using high-throughput screening assays. Toxicogenomic databases store gene expression profiles after chemical exposure. Other databases store manually-curated interactions between chemicals and proteins. However, each dataset probes a different dimension of cell's response. Moreover, these experiments ignore complex networks through which proteins interact and computational methods to integrate these data are underdeveloped. These major barriers limit the usefulness of these data.

Our goal is to build chemical signaling networks by connecting chemically-perturbed receptors to transcription factors (TFs) through the human protein interaction network using the PathLinker algorithm, and evaluate these networks using statistical significance and functional enrichment methods. These networks may reveal important intermediate proteins or physiological processes not previously implicated with the chemical. For toxicologists to use these networks in their research, we will make them available on GraphSpace. Check out the 5-Fluorouracil signaling network.

Here is the poster I presented at the 2017 International Conference on Systems Biology: