Thermo Fisher and SRI International extend small molecule research


Thermo Fisher Scientific and SRI International collaborate to enable researchers to combine the results of high resolution Orbitrap LC/MS experiments, with highly curated and organism specific metabolic pathway and genome data for quick and effective mass spectrometry based small molecule research and analysis

The outcome of a successful collaboration, researchers now have a direct link between the Thermo Scientific Compound Discoverer 2.1 software platform for small molecule research and SRI International’s BioCyc, a collection of 9300 databases providing electronic reference sources on the metabolic pathways and genomes of many organisms.

Peter Karp, Director of Bioinformatics Research Group at SRI International, said: “We are delighted to bring the power of BioCyc to Thermo Fisher’s customers through a system that is intuitive and easy to use.

Scientists can now follow a link from Compound Discoverer to a BioCyc metabolic pathway page to gain access to a comprehensive knowledge hub of genome and pathway information.

The ability to automatically and interactively overlay statistical data onto these pathways can facilitate the biological interpretation of results obtained from a metabolomics experiment.

Ultimately, this new link is expected to speed data analysis for Compound Discoverer users and enable them to visualise many individual compound measurements to gain a comprehensive understanding of biological processes in an experiment.

Andreas Huhmer, Director Proteomics and Metabolomics Marketing, Chromatography and Mass Spectrometry at Thermo Fisher, said: “Today, metabolomics researchers can measure thousands of small molecules, but it can be challenging to know, which cellular systems are behaving differently in the studied condition compared to a control.

"The new integration will allow scientists using Compound Discoverer to automatically map the most detected compounds to BioCyc metabolic pathway diagrams, and to connect additional experimental data, such as relative abundance or differential expression, onto the pathways.”

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