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Agilent Releases GeneSpring 1.1, Closes Stratagene in Bid to Grow Life-Sciences Play

Agilent this week debuted a new version of its GeneSpring biomarker discovery tool for mass spec data.
Version 1.1 of the software enables researchers to import data produced by the company’s 6410 triple quadrupole liquid chromatography/mass spectrometer system.
GeneSpring MS 1.1, which supports data files in the exchange format mzXML, will allow customers to actually use myriad mass spectrometers and to standardize their biomarker discovery workflow, enabling the discovery of protein and metabolite biomarkers.
Agilent product manager Thon De Boer told BioInform that the new platform differs from the company’s Mass Hunter in that Mass Hunter is more of a data-analysis tool, mostly focused on a given number of individual files.
“There is functionality within Mass Hunter which can deal with more batch analysis,” he said. GeneSpring 1.1, on the other hand, “is more batch analysis(-oriented), using statistics and algorithms to find differences and abundances of these biomarkers.”
GeneSpring MS version 1.1 users will be able to profile data rather than take the standard approach of simply identifying data in advance.

“Most of the portfolio [from Stratagene] really interfaces very well; a lot of the reagents they make [complement Agilent’s life science products].”

“If you do identification first you may not find everything because due to the technology you might not be able to get the [right or correct] identity for all the peptides you have in your sample [for example],” De Boer said, adding that with the profiling approach, “you have a much larger pool to draw from.”
The profiling approach afforded by version 1.1 gives researchers an increased ability to figure out what the peptides actually represent, and then follow up.
“So we are able to look for differences from one group to the next using a number of statistics, clustering, and class tools and focus on limiting the list,” said De Boer.

Researchers can “start with hundreds of thousands of biomarkers and … want to end up with a handful, [in order] to figure out what the peptides really represent. And then [they] follow up with the biomarker validation study in which [they] do hundreds of thousands of samples, but only focus on a handful.”


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