ArticleExperimental physiology2024
Network model of skeletal muscle cell signalling predicts differential responses to endurance and resistance exercise training.
Article in Experimental physiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 12 citations in OpenAlex.
- Systems modelling of mitochondrial dynamics in different exercise regimes.The Journal of physiology · 2026Article
- Mechanochemical modeling of exercise-induced skeletal muscle hypertrophy.PLoS computational biology · 2026Article
- Interplay between store-operated calcium entry and mitochondrial phosphate handling modulates force and fatigue during exercise.bioRxiv : the preprint server for biology · 2026Article
- Modeling the interplay of sex hormones in cardiac hypertrophic signaling.PLoS computational biology · 2025Article
- Systems modeling and uncertainty quantification of AMP-activated protein kinase signaling.NPJ systems biology and applications · 2025Article
- The Evolution of Systems Biology and Systems Medicine: From Mechanistic Models to Uncertainty Quantification.Annual review of biomedical engineering · 2025Review
- Logic-based modeling of biological networks with Netflux.PLoS computational biology · 2025Article
- The multifaceted impact of physical exercise on FoxO signaling pathways.Frontiers in cell and developmental biology · 2025Review
- Network model of skeletal muscle cell signalling predicts differential responses to endurance and resistance exercise training.Experimental physiology · 2024Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
Exercise-induced muscle adaptations vary based on exercise modality and intensity. We constructed a signalling network model from 87 published studies of human or rodent skeletal muscle cell responses to endurance or resistance exercise in vivo or simulated exercise in vitro. The network comprises 259 signalling interactions between 120 nodes, representing eight membrane receptors and eight canonical signalling pathways regulating 14 transcriptional regulators, 28 target genes and 12 exercise-induced phenotypes. Using this network, we formulated a logic-based ordinary differential equation model predicting time-dependent molecular and phenotypic alterations following acute endurance and resistance exercises. Compared with nine independent studies, the model accurately predicted 18/21 (85%) acute responses to resistance exercise and 12/16 (75%) acute responses to endurance exercise. Detailed sensitivity analysis of differential phenotypic responses to resistance and endurance training showed that, in the model, exercise regulates cell growth and protein synthesis primarily by signalling via mechanistic target of rapamycin, which is activated by Akt and inhibited in endurance exercise by AMP-activated protein kinase. Endurance exercise preferentially activates inflammation via reactive oxygen species and nuclear factor κB signalling. Furthermore, the expected preferential activation of mitochondrial biogenesis by endurance exercise was counterbalanced in the model by protein kinase C in response to resistance training. This model provides a new tool for investigating cross-talk between skeletal muscle signalling pathways activated by endurance and resistance exercise, and the mechanisms of interactions such as the interference effects of endurance training on resistance exercise outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.