Distributed computing and data storage in proteomics: many hands make light work, and a stronger memory
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Updated: May 5, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Kenneth Verheggen1, Harald Barsnes, Lennart Martens
1Department of Medical Protein Research, VIB, Ghent, Belgium; Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium.
Abstract:
Modern day proteomics generates ever more complex data, causing the requirements on the storage and processing of such data to outgrow the capacity of most desktop computers. To cope with the increased computational demands, distributed architectures have gained substantial popularity in the recent years. In this review, we provide an overview of the current techniques for distributed computing, along with examples of how the techniques are currently being employed in the field of proteomics. We thus underline the benefits of distributed computing in proteomics, while also pointing out the potential issues and pitfalls involved.

