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The issue
Research projects across the globe create huge amounts of data. Teams can spend hundreds of hours interrogating that data and creating different visualisations to help them identify correlations and relationships.
At the end of the project the data is often left on a hard drive, never to be used again. If it could be made available to the global research community in a usable and searchable way, the impact of the data is multiplied and it becomes a valuable resource beyond the scope of the project.
The research
Researchers from the Department of Biology at the University of York investigated how microbes respond to the stresses of bioproduction, with the aim of reducing our dependence on petrochemicals to create a greener, more sustainable future.
“As part of the Project DETOX we collected vast amounts of data to help us understand the physiological changes that microbes use to survive when exposed to bio-manufacturing chemicals that are toxic to them,” said Professor Gavin Thomas, Chair in Microbiology. “We needed to be able to take this data and model the stress process and created a data analysis tool to support this.
“We soon realised that we’d created a tool that could be scaled up and made available to others. It could help them visualise their data or provide new perspectives on data already in the database.”
The Project DETOX data tool was developed into MORF, a web-based platform for visualising complex biological data.
The outcome
With MORF, the team has created an intuitive bioinformatics tool that makes big data accessible to everyone.
“Using MORF enables academics to disseminate their research in an interactive platform rather than a static table in a journal,” added Professor Thomas. “It helps organisations in industry who want to bring multiple data sets together to compare them more easily and identify correlations and improve production.”
One of the early adopters of MORF is Robson Tramontina, an Associate Researcher at the State University of Campinas who used the platform for analysis of yeast gene expression. “Using MORF has enhanced our efficiency by approximately 40%,” he says. “This reflects the reduction in time spent on manual data interpretation and the increased ease of accessing vital information through the platform. MORF is very user friendly, you can easily access external links and it makes my life much easier.”
