Gbrowse Moby: a Web-based browser for BioMoby Services

Mark Wilkinson

Assistant Professor, Department of Medical Genetics, University of British Columbia, James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St. Paul's Hospital, Rm. 166, 1081 Burrard St., Vancouver, BC, V6Z 1Y6, Canada

author email corresponding author email

Source Code for Biology and Medicine 2006, 1:4doi:10.1186/1751-0473-1-4


Published:	24 October 2006

Abstract

Background

The BioMoby project aims to identify and deploy standards and conventions that aid in the discovery, execution, and pipelining of distributed bioinformatics Web Services. As of August, 2006, approximately 680 bioinformatics resources were available through the BioMoby interoperability platform. There are a variety of clients that can interact with BioMoby-style services. Here we describe a Web-based browser-style client – Gbrowse Moby – that allows users to discover and "surf" from one bioinformatics service to the next using a semantically-aided browsing interface.

Results

Gbrowse Moby is a low-throughput, exploratory tool specifically aimed at non-informaticians. It provides a straightforward, minimal interface that enables a researcher to query the BioMoby Central web service registry for data retrieval or analytical tools of interest, and then select and execute their chosen tool with a single mouse-click. The data is preserved at each step, thus allowing the researcher to manually "click" the data from one service to the next, with the Gbrowse Moby application managing all data formatting and interface interpretation on their behalf. The path of manual exploration is preserved and can be downloaded for import into automated, high-throughput tools such as Taverna. Gbrowse Moby also includes a robust data rendering system to ensure that all new data-types that appear in the BioMoby registry can be properly displayed in the Web interface.

Conclusion

Gbrowse Moby is a robust, yet facile entry point for both newcomers to the BioMoby interoperability project who wish to manually explore what is known about their data of interest, as well as experienced users who wish to observe the functionality of their analytical workflows prior to running them in a high-throughput environment.