5374b305_Symposium__Boston__August_2010__2
[0] 15:45 [1] Qian Zhu [2] 
Mining and visualizing chemical compound−specific Chemical−Gene/Disease/Pathway/Literature relationships Abstract In common with most scientific disciplines, there has in the last few years been a huge increase in the amount of publicly−available and proprietary information pertinent to drug discovery, owing to a variety of factors including improvements in experimental technologies. So the big challenge for us is how we can use all of this information together in an intelligent way, in an integrative fashion. We are developing an application to mine relationships between Chemical and Gene/Disease/Pathway/Literature, and visualize them. It aims to help answer the question “anything else should I know about this compound?” from a medicinal chemistry perspective based on the full picture of chemicals. For the mining part, we have already developed an aggregating web services, named WENDI, which calls multiple individual or atomic, web services including diversity of compound−related data sources, predictive models and self−developed algorithms, and aggregates the results from these services in XML; For visualizing, two ways to go: First, we create a RDF reasoner to convert XML from WENDI to RDF, find inferred relationships based on RDF, rank evidences focused on chemical−disease, and print all evidences out by using SWP faceted browser based on Longwell http://simile.mit.edu/wiki/Longwell), it mixes the flexibility of the RDF data model with the faceted browser to enable users to browse complex RDF triples in a user−friendly and meaningful manner; Second, we place all relationships from WENDI into a chemical space consisted of 60M PubChem compounds, then clustered/highlighted particular chemical compounds with specific attributes, like gene/disease/pathway/literature by using PubChemBrowse, which is a customized visualization tool for cheminformatics research and provides a novel 3D data point browser that displays complex properties of massive data on commodity clients and supports fast interaction with an external property database via semantic web interface. PDF
ACS RDF Symposium, Boston, August 2010
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