Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli

Abstract

Multi-omics data integration is a great challenge. Here, the authors compile a database of E. coliproteomics, transcriptomics, metabolomics and fluxomics data to train models of recurrent neural network and constrained regression, enabling prediction of bacterial responses to perturbations.