Email updates

Keep up to date with the latest news and content from BMC Bioinformatics and BioMed Central.

This article is part of the supplement: European Molecular Biology Network (EMBnet) Conference 2008: 20th Anniversary Celebration. Leading applications and technologies in bioinformatics

Open Access Proceedings

Visualising biological data: a semantic approach to tool and database integration

Steve Pettifer1*, David Thorne12, Philip McDermott13, James Marsh12, Alice Villéger12, Douglas B Kell2 and Teresa K Attwood13

Author Affiliations

1 School of Computer Science, University of Manchester, Manchester, M13 9PL, UK

2 School of Chemistry, University of Manchester, Manchester, M13 9PL, UK

3 Faculty of Life Sciences, University of Manchester, Manchester, M13 9PL, UK

For all author emails, please log on.

BMC Bioinformatics 2009, 10(Suppl 6):S19  doi:10.1186/1471-2105-10-S6-S19

Published: 16 June 2009

Abstract

Motivation

In the biological sciences, the need to analyse vast amounts of information has become commonplace. Such large-scale analyses often involve drawing together data from a variety of different databases, held remotely on the internet or locally on in-house servers. Supporting these tasks are ad hoc collections of data-manipulation tools, scripting languages and visualisation software, which are often combined in arcane ways to create cumbersome systems that have been customised for a particular purpose, and are consequently not readily adaptable to other uses. For many day-to-day bioinformatics tasks, the sizes of current databases, and the scale of the analyses necessary, now demand increasing levels of automation; nevertheless, the unique experience and intuition of human researchers is still required to interpret the end results in any meaningful biological way. Putting humans in the loop requires tools to support real-time interaction with these vast and complex data-sets. Numerous tools do exist for this purpose, but many do not have optimal interfaces, most are effectively isolated from other tools and databases owing to incompatible data formats, and many have limited real-time performance when applied to realistically large data-sets: much of the user's cognitive capacity is therefore focused on controlling the software and manipulating esoteric file formats rather than on performing the research.

Methods

To confront these issues, harnessing expertise in human-computer interaction (HCI), high-performance rendering and distributed systems, and guided by bioinformaticians and end-user biologists, we are building reusable software components that, together, create a toolkit that is both architecturally sound from a computing point of view, and addresses both user and developer requirements. Key to the system's usability is its direct exploitation of semantics, which, crucially, gives individual components knowledge of their own functionality and allows them to interoperate seamlessly, removing many of the existing barriers and bottlenecks from standard bioinformatics tasks.

Results

The toolkit, named Utopia, is freely available from http://utopia.cs.man.ac.uk/ webcite.