Open Access Highly Accessed Software

WENDI: A tool for finding non-obvious relationships between compounds and biological properties, genes, diseases and scholarly publications

Qian Zhu1, Michael S Lajiness2, Ying Ding3 and David J Wild1*

Author Affiliations

1 School of Informatics and Computing, Indiana University, Bloomington, IN, USA

2 Eli Lilly and Company, Indianapolis, IN, USA

3 School of Library & Information Science, Indiana University, Bloomington, IN, USA

For all author emails, please log on.

Journal of Cheminformatics 2010, 2:6  doi:10.1186/1758-2946-2-6

Published: 20 August 2010

Abstract

Background

In recent years, there has been a huge increase in the amount of publicly-available and proprietary information pertinent to drug discovery. However, there is a distinct lack of data mining tools available to harness this information, and in particular for knowledge discovery across multiple information sources. At Indiana University we have an ongoing project with Eli Lilly to develop web-service based tools for integrative mining of chemical and biological information. In this paper, we report on the first of these tools, called WENDI (Web Engine for Non-obvious Drug Information) that attempts to find non-obvious relationships between a query compound and scholarly publications, biological properties, genes and diseases using multiple information sources.

Results

We have created an aggregate web service that takes a query compound as input, calls multiple web services for computation and database search, and returns an XML file that aggregates this information. We have also developed a client application that provides an easy-to-use interface to this web service. Both the service and client are publicly available.

Conclusions

Initial testing indicates this tool is useful in identifying potential biological applications of compounds that are not obvious, and in identifying corroborating and conflicting information from multiple sources. We encourage feedback on the tool to help us refine it further. We are now developing further tools based on this model.

Graphical abstract