{"id":"W4361255792","doi":"10.1371/journal.pcbi.1010690","title":"Network models of protein phosphorylation, acetylation, and ubiquitination connect metabolic and cell signaling pathways in lung cancer","year":2023,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"National Institute of Dental and Craniofacial Research; National Institute of General Medical Sciences; National Cancer Institute; National Institutes of Health; University of Montana; Bristol-Myers Squibb; H. Lee Moffitt Cancer Center and Research Institute; Moffitt Cancer Center","keywords":"Crosstalk; Biology; Signal transduction; Phosphoproteomics; Stable isotope labeling by amino acids in cell culture; Cell biology; Proteomics; Metabolic pathway; Phosphorylation; Computational biology; Biochemistry; Protein phosphorylation; Protein kinase A","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005023585,0.000474823,0.0003236537,0.001390021,0.0003131707,0.0006436608,0.0004809492,0.0003968051,0.001122337],"category_scores_gemma":[0.001448359,0.0002570479,0.000725495,0.001227157,0.0004199144,0.0008004862,0.0004295349,0.0003077246,0.0001241046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001292087,"about_ca_system_score_gemma":0.0004861546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008211048,"about_ca_topic_score_gemma":0.008517578,"domain_scores_codex":[0.9997604,0.00008746023,0.00001021935,0.00008051108,0.00003513025,0.00002612192],"domain_scores_gemma":[0.9993747,0.0003598082,0.0001320885,0.00003995434,0.00005450497,0.00003887163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001227943,0.00003985948,0.01217734,0.0000954025,0.000177322,0.0001694667,0.0001157789,0.953948,0.006528519,0.01496173,0.0005184128,0.01114537],"study_design_scores_gemma":[0.000006317962,0.00002277969,0.005919364,0.000005801283,0.00003245227,0.00005125127,0.00002785338,0.9765658,0.0004733209,0.01630048,0.0005874201,0.000007118015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7347883,0.001304052,0.2556185,0.0007617165,0.00001618654,0.0001083063,0.002572743,0.0004958456,0.004334345],"genre_scores_gemma":[0.9697854,0.0006639871,0.02662186,0.00004651021,0.00001139041,0.0001214431,0.001369861,0.00002733433,0.001352121],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008211048,"threshold_uncertainty_score":0.01632649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01557796264716729,"score_gpt":0.2348005063259546,"score_spread":0.2192225436787873,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}