Teaching 'big data' analysis to young immunologists

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Abstract

Imagine two immunologists, Bill and Steve, who meet in 2030. Steve asks, “Bill, how is your science going?” Bill answers, “We now have access to 500 petabytes of storage, a 100,000-node GPU computer cluster with 500 terabyte RAM, and the newest data-integration engine that allows us to instantaneously access all publically available data collections worldwide. We finally generate and prioritize our hypotheses based on big data.” There are numerous developments already ongoing that make this scenario very real. The big data revolution incorporates the 'three Vs': volume of data, velocity of processing the data, and variability of data sources; therefore, preparation is required to take advantage of the technological advances and tools available to efficiently interrogate large data sets to maximal effect. Indeed, every immunologist will have access to high-quality and publically available big data regarding primary immune cells from numerous species. Though they will not need to become computer scientists per se, young immunologists will need to know how to make use of the wealth of data that are currently being generated and that are anticipated in the coming decades, and thus training will be required not only in molecular and systems immunology but also in big data science. This will require changes in graduate and undergraduate education in order to achieve the goals of training students to embrace the big data era of science and teaching them how to use vast data resources in hypothesis generation. Here, I will discuss some of the developments in big data science, its impact on immunology and how we need to adapt our education programs to cope with the expected changes.

 

PublikationTeaching 'big data' analysis to young immunologistsNature Immunology, DOI: doi:10.1038/ni.3250