Real-time processing of proteomics data: The internet of things and the connected laboratory

Processing data from life sciences experiments presents many challenges, these include the volume of data to be processed and the complexity of the processing needed in order to present meaningful results back to the experimenters. This is particularly evident in the field of proteomics where the complex datasets provided by mass spectrometers require extensive preprocessing and the use of search algorithms before they can be used effectively. Many tools currently exist to carry out this processing but they are focused on batch based workloads where the mass spectrometer finishes its analysis and then the data is processed on a file by file basis. Usually this work is carried out on local PC hardware, which can also cause a data management problem. The research described in this paper leads to a distributed cluster-based architecture designed to process the mass spectrometer output in a real-time streaming fashion. In this way the mass spectrometers in a laboratory together with a central computing platform constitute an internet of things problem which can be solved using modern open-source technology and cloud computing.