Phosphorylation of skeletal muscle proteins mediates cellular signaling and adaptive responses to exercise. Bioinformatic and machine learning approaches identified preclinical models that recapitulate human exercise responses. Feature selection showed that muscles from treadmill running mice and maximum intensity contractions shared the most differentially phosphorylated phosphosites (DPPS) with human exercise. Benefits of exercise in chronic diseases may be reduced by hyperammonemia, a consistent perturbation in chronic diseases and a muscle cytotoxin generated during contractile activity. Comparative analysis of experimentally validated molecules identified 63 DPPS on 265 differentially expressed phosphoproteins (DEpP) shared between hyperammonemia in myotubes and skeletal muscle from exercise models. Functional enrichment analyses revealed distinct temporal patterns of enrichment shared between hyperammonemia and exercise models including protein kinase A(PKA), calcium signaling, mitogen activated protein kinase(MAPK) signaling, and protein homeostasis. Our approach of feature extraction of comparative unbiased data allows for model selection and target identification to optimize responses to interventions.