Skeletal muscle is the principal contributor to exercise-induced changes in human metabolism. Strikingly, although it has been demonstrated that a lot of metabolites accumulating in blood and human skeletal muscle during an exercise activate different signaling pathways and induce expression of many genes in working muscle fibres, the system understanding of signaling-metabolic pathways interrelations with downstream genetic regulation in the skeletal muscle is still elusive. Herein, a physiologically based computational model of skeletal muscle comprising energy metabolism, Ca2+ and AMPK signalling pathways, and expression regulation of genes with early and delayed responses has been developed based on a modular modeling approach. The integrated modular model validated on diverse including original experimental data and different exercise modes provides a comprehensive in silico platform in order to decipher and track cause-effect relationships between metabolic, signaling and gene expression levels in the skeletal muscle.