The field of proteomics presents scientists with many unexpected challenges. Not only are they faced with analyzing complex samples, seeking to achieve an unprecedented number of targets, but the increasingly large volume of data, due to information richer files and study size, are becoming an obstacle in data processing performance and leading to siloed storage.
Finally, there is now a solution for management, automation, processing and sharing of proteomics data sets. Powered by modern cloud technology, automation, and artificial intelligence, you can accelerate time-to-results, extract deeper insights, and effortlessly communicate findings to collaborators, enabling you to get closer to the truth.
How to efficiently manage, automate, rapidly process, and share large proteomics data sets using a cloud-native platform with cutting-edge proteome software tools.
David Horn, Senior Product Manager, Thermo Fisher Scientific
David is the product manager of the Thermo Scientific Proteome Discoverer software and has previously managed the Protein Deconvolution and ProSightPC software products. He also has experience as an algorithm developer/software scientist. He earned his Ph.D. at Cornell University in the McLafferty lab developing new acquisition methods and algorithms for top-down protein characterization.
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