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arXiv · 2001.04794

A machine learning approach to investigate regulatory control circuits in bacterial metabolic pathways

Francesco Bardozzo·Pietro Lio'·Roberto Tagliaferri
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Abstract

In this work, a machine learning approach for identifying the multi-omics metabolic regulatory control circuits inside the pathways is described. Therefore, the identification of bacterial metabolic pathways that are more regulated than others in term of their multi-omics follows from the analysis of these circuits . This is a consequence of the alternation of the omic values of codon usage and protein abundance along with the circuits. In this work, the E.Coli's Glycolysis and its multi-omic circuit features are shown as an example.

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Francesco Bardozzo, Pietro Lio', Roberto Tagliaferri. 2020-01-13. A machine learning approach to investigate regulatory control circuits in bacterial metabolic pathways. https://doi.org/10.1093/bioinformatics/btaa966

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