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Lund University develops test alternatives thanks to unique software

By Michelle Yeomans+

10-Apr-2013
Last updated on 10-Apr-2013 at 12:18 GMT

Lund University develops test alternatives thanks to unique software

Swedish researchers at Lund University have developed various in vitro test strategies to replace animal testing when determining skin allergens, thanks to a special special gene expression analysis software.

A collaborative research project referred to as 'Qlucore' between the University and researchers at the Department of Mathematics and Clinical Genetics features a group 'Sens-it-iv', that is dedicated to the development of in vitro (‘out of body’) test strategies that could reduce or replace animal testing for sensitization studies.

Of that venture, a special software 'Qlucore Omics Explorer 2.0' was developed by scientists involved that say represents a major step forward in the study of allergens, alongwith the added support for hierarchical clustering, scatter plots and powerful log function.

"It was recognised that an interactive scientific software tool was needed to conceptualise the ideas evolving from the research collaboration.Thus this combination of instant visualisation and advanced statistics support gives the user new opportunities. All user action is at most two mouse clicks away."

Beneficial technology in skin care research

According to one of the researchers, Dr. Albrekt, the basic concept behind the software is to provide a tool that can take full advantage of the most powerful pattern recogniser that exists; the human brain. Thus, the technology was designed with a core software engine that visualises the data in 3D and aids the user in identifying hidden structures and patterns.

In the area of allergy testing, the scientist says despite gene expression studies proving to be invaluable, the amount of data that is produced by these type of experiments is enormous and that as a result, it is impossible to derive any real biological meaning from these findings unless sophisticated data algorithms are used to help interpret this data effectively.

And it is for this reason Albrekt says this technology works better than other softwares, as they have been designed to mainly focus on the ability to handle increasingly vast amounts of data, which means that the role of the scientist/researcher has been largely set aside and that as a result, a lot of data analysis has been passed on to bioinformaticians and biostatisticians.

"In our studies, we are dealing with very large amounts of data, sometimes between 10 and 100 million data points, which we tend to view as graphics."

"With other software, these graphics would take a long time to appear, but with the latest data analysis tools, the information is presented instantly. As a result, we can be much more creative with our theories, as we can easily test any number of hypotheses in rapid succession," she concludes.

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