TY - CHAP
T1 - The Disruptive 4IR in the Life Sciences
T2 - Metabolomics
AU - Tugizimana, Fidele
AU - Engel, Jasper
AU - Salek, Reza
AU - Dubery, Ian
AU - Piater, Lizelle
AU - Burgess, Karl
N1 - Publisher Copyright:
© 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Artificial intelligence (AI)
KW - Big data
KW - Cloud computing
KW - Cloud metabolomics
KW - Fourth industrial revolution—4IR
KW - Machine learning
KW - Metabolomics
UR - http://www.scopus.com/inward/record.url?scp=85088458006&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-48230-5_10
DO - 10.1007/978-3-030-48230-5_10
M3 - Chapter
AN - SCOPUS:85088458006
T3 - Lecture Notes in Electrical Engineering
SP - 227
EP - 256
BT - Lecture Notes in Electrical Engineering
PB - Springer
ER -