![]() ![]() The above examples only underscore one aspect of big data: big numbers, but big data challenges are much more complex than dealing with large scale datasets. ![]() According to a recent report, this volume of genomics data will surpass that of YouTube, Twitter, and the future Square Kilometre Array by 2025 ( 21). Genomics, which is driven by massively-paralleled DNA sequencers ( 20), is currently feeling the burden of big data, with a projected 2–40 million terabytes of genomic data being generated in the next ten years, representing anywhere from 100 million to 2 billion complete human genomes sequenced. To address this formidable challenge, researchers are turning to high-throughput screening using MS-based assays which are capable of screening up to 100,000 compounds a day from combinatorial small molecule libraries ( 18, 19). Drug discovery initiatives are aimed at finding the proverbial needles in haystacks in a molecular landscape of over 10 60 possible chemical structures ( 15, 16), which is a haystack containing a novemdecillion straws of hay, or about 40 orders-of-magnitude greater than the number of grains of sand on Earth ( 17). ![]() Another grand challenge, systems biology, seeks to form connections between all of the various classes of biomolecules in both space and time towards the comprehensive diagnosis of disease states ( 11), and MS is at the forefront of integrated omics approaches that will help realize this vision ( 12, 13, 14). The human metabolome is represented by many diverse classes of small molecule metabolites, of which a little over 40,000 have been annotated so far with support from MS techniques ( 7, 8, 9), but estimates place the possible number of human metabolites as high as 180,000 for lipids alone ( 10). The inclusion of spatially-resolved protein information from imaging studies will increase this number even further ( 6). Proteomics seeks to detect and measure all proteins found in an organism ( 1), which based on several recent drafts, numbers between 16,000 and 19,000 for basic human proteins ( 2, 3, 4), but could be as high as several million once protein variants and modifications are taken into account ( 5). All grand challenges where mass spectrometry (MS) plays a role are characterized by the big data paradigm ( Table 1). ![]()
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