The Disruptive 4IR in the Life Sciences: Metabolomics

Fidele Tugizimana, Jasper Engel, Reza Salek, Ian Dubery, Lizelle Piater, Karl Burgess

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

12 Citations (Scopus)


A new era of systems biology is disruptively emerging, holistically describing biochemical events at both organismal and cellular level. In this new era, emerging ‘-omics’ technologies have brought about a paradigm shift in biological sciences and research. Metabolomics, the youngest of the omics trilogy and defined as the qualitative and quantitative investigation of the entire metabolome of a biological system, has positioned itself as an indispensable methodology to investigate global biochemistry phenomena at a cellular level. Metabolomics is a multidisciplinary research field, involving a convergence of biology, chemistry, chemometrics, statistics and computer science. Metabolomics accordingly can provide unprecedented in-depth explanations and insights of the mechanisms responsible for various physiological conditions, given the innovative developments in analytical technologies (integrating artificial intelligence and machine learning), advancement in chemometric and statistical methods (big data analytics and management), and the integration of orthogonal biological approaches. Thus, the objective of this Chapter is to provide an overview of 4IR in life sciences, illustratively pointing to some aspects in the metabolomics field. The latter, in its ontology, applies different 4IR technologies including big data analytics, machine learning, cloud computing, and artificial intelligence, amongst others. The momentum and maturation of metabolomics is undeniably evident, positively disruptive, and the field has visibly revolutionised the life sciences. The application of metabolomics spans a wide spectrum of the afore-said sciences, including biomedical technology, natural products, and plant biochemistry and—biotechnology research to name a few.

Original languageEnglish
Title of host publicationLecture Notes in Electrical Engineering
Number of pages30
Publication statusPublished - 2020

Publication series

NameLecture Notes in Electrical Engineering
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119


  • Artificial intelligence (AI)
  • Big data
  • Cloud computing
  • Cloud metabolomics
  • Fourth industrial revolution—4IR
  • Machine learning
  • Metabolomics

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering


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