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Big Data in Modern Chemical Analysis

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Abstract

A review of scientific publications covering the acquisition and use of big data in modern analytical chemistry is presented. Such data are characterized by considerable volumes, flows, and variety. Their generation and manipulations with them accompany the analysis of biosamples and samples of other origin by chromatography and mass spectrometry. Big data obtained by these techniques ensure multianalyte sample analysis, though the characteristics of the detection, identification, and quantification are satisfactory not for all analytes. The application of simple analytical systems can also be accompanied by the accumulation of big data volumes. A huge body of information is contained in big chemical databases, the use of which is necessary in non-target analysis. The selection of candidates for identification takes into account the prevalence (citation rate) of chemicals; identification includes the use of reference mass spectral libraries. Methods of data processing, analysis, and presentation (statistics, chemometrics) evolve with the growth of the volume of information. Technical characteristics of computers and their networks are improved at advancing rates, creating a potential for the development of methods of data analysis and opening new possibilities for interlaboratory cooperation.

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Notes

  1. “Information” and “data” are often considered similar notions. More exactly, “data” are “raw materials”, and “information” is processed data (see, for example, [2]).

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Authors and Affiliations

  1. Institute of Experimental Medicine, 197376, St. Petersburg, Russia

    B. L. Milman

  2. Institute of Toxicology, Federal Biomedical Agency of Russia, 192019, St. Petersburg, Russia

    I. K. Zhurkovich

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  1. B. L. Milman
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  2. I. K. Zhurkovich
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Correspondence to B. L. Milman or I. K. Zhurkovich.

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Translated by E. Rykova

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Milman, B.L., Zhurkovich, I.K. Big Data in Modern Chemical Analysis . J Anal Chem 75, 443–452 (2020). https://doi.org/10.1134/S1061934820020124

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