Pesticides : Chemical Similarity Networks and Data Table
A list of 980 pesticides was queried against publicly available databases to retrieve published data and literature on chemical's carcinogenic potential in animal experiments and epidemiological settings. The complexity of the data was visualized using chemical similarity network graphs which allowed extension of existing classification schemes, such as the one obtained from KEGG, and provided an efficient way to visualize the retrieved rich information. To highlight the application for selecting candidates for IARC Monographs evaluation, pesticides containing chlorine and phosphorus atoms, including the two of the most commonly used pesticide classes of organocholorines and organophosphates, were visualized as focused network graphs. High-ranked pesticides were then further passed through additional pesticide specific filter to create a final list of selected agents. Additionally, an interactive data table is provided at the bottom of graphs with hyperlinks that redirect queries to the PubMed database to retrieve the most recent publications.
Citation : Neela Guha,Kate Guyton, Dana Loomis, Dinesh Kumar Barupal, Prioritizing chemicals for risk asssement using chemoinformatics : examples from the IARC monographs on Pesticides. Environ Health Perspect; 2016 DOI:10.1289/EHP186
