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

Authors
Bardozzo, Francesco 
Lio', Pietro 
Tagliaferri, Roberto 

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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.

Publication Date
2020
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Keywords
q-bio.MN, q-bio.MN, cs.LG, stat.ML
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CIBB
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Volume Title
2016
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All rights reserved