Being able to explore the metabolism of broad metabolizing cells is of critical importance in many 20 research fields. This article presents an original modelling solution combining metabolic network 21 and omics data to identify modulated metabolic pathways and changes in metabolic functions 22 occurring during differentiation of a human hepatic cell line (HepaRG). Our results confirm the 23 activation of hepato-specific functionalities and newly evidence modulation of other metabolic 24 pathways, which could not be evidenced from transcriptomic data alone. Our method takes 25 advantage of the network structure to detect changes in metabolic pathways that do not have gene 26 annotations, and exploits flux analyses techniques to identify activated metabolic functions. 27 Compared to usual cell-specific metabolic network reconstruction approaches, it limits false 28 predictions by considering several possible network configurations to represent one phenotype, 29 rather than one arbitrarily selected network. Our approach significantly enhances the 30 comprehensive and functional assessment of cell metabolism, opening further perspectives to 31 investigate metabolic shifts occurring within various biological contexts.