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This article is part of the supplement: Selected articles from the IEEE International Conference on Bioinformatics and Biomedicine 2010

Open Access Open Badges Proceedings

The BioAssay network and its implications to future therapeutic discovery

Jintao Zhang1, Gerald H Lushington2 and Jun Huan3*

Author Affiliations

1 Center for Bioinformatics, University of Kansas, Lawrence, KS 66045, USA

2 Molecular Graphics & Modeling Lab, University of Kansas, Lawrence, KS 66045, USA

3 Department of Electrical Engineering & Computer Science, University of Kansas, Lawrence, KS 66045, USA

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BMC Bioinformatics 2011, 12(Suppl 5):S1  doi:10.1186/1471-2105-12-S5-S1

Published: 27 July 2011



Despite intense investment growth and technology development, there is an observed bottleneck in drug discovery and development over the past decade. NIH started the Molecular Libraries Initiative (MLI) in 2003 to enlarge the pool for potential drug targets, especially from the “undruggable” part of human genome, and potential drug candidates from much broader types of drug-like small molecules. All results are being made publicly available in a web portal called PubChem.


In this paper we construct a network from bioassay data in PubChem, apply network biology concepts to characterize this bioassay network, integrate information from multiple biological databases (e.g. DrugBank, OMIM, and UniHI), and systematically analyze the potential of bioassay targets being new drug targets in the context of complex biological networks. We propose a model to quantitatively prioritize this druggability of bioassay targets, and literature evidence was found to confirm our prioritization of bioassay targets at a roughly 70% accuracy.


Our analysis provide some measures of the value of the MLI data as a resource for both basic chemical biology research and future therapeutic discovery.