{"id":"W1975891365","doi":"10.1186/gm32","title":"Applications of metabolomics and proteomics to the mdx mouse model of Duchenne muscular dystrophy: lessons from downstream of the transcriptome","year":2009,"lang":"en","type":"article","venue":"Genome Medicine","topic":"Muscle Physiology and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"","keywords":"Duchenne muscular dystrophy; Proteomics; Dystrophin; Muscular dystrophy; Metabolomics; Biology; Transcriptome; Computational biology; mdx mouse; Functional genomics; Systems biology; Genomics; Bioinformatics; Skeletal muscle; DNA microarray; Genetics; Genome; Anatomy; Gene; Gene expression","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":[0.001748794,0.000883635,0.001187582,0.00177109,0.0003408586,0.001422942,0.000619676,0.001380319,0.000748048],"category_scores_gemma":[0.0008154028,0.0004432787,0.0008202872,0.0009515184,0.001800764,0.002432363,0.001273599,0.004964722,0.0004053282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006894427,"about_ca_system_score_gemma":0.0006251629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007487276,"about_ca_topic_score_gemma":0.001168654,"domain_scores_codex":[0.9994243,0.0001778539,0.00005447358,0.0001368911,0.0001571138,0.00004940318],"domain_scores_gemma":[0.9993911,0.0002198921,0.00007903526,0.00007477914,0.0001499673,0.00008528472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000610538,0.0001948356,0.00520265,0.003288425,0.0002831327,0.001808607,0.0008016436,0.001729617,0.6238295,0.05922912,0.01204446,0.2909774],"study_design_scores_gemma":[0.0001209419,0.002385773,0.04808458,0.002261471,0.000442578,0.009400606,0.002039137,0.007274911,0.2662262,0.1782105,0.4830747,0.0004785346],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.09972047,0.4135558,0.3879559,0.07274426,0.003549355,0.000189305,0.001410279,0.001317297,0.01955736],"genre_scores_gemma":[0.2599264,0.432641,0.2680756,0.02396229,0.003159395,0.0003399778,0.001006528,0.0004750983,0.01041371],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00177109,"threshold_uncertainty_score":0.009248674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009506752867966557,"score_gpt":0.2386402471977682,"score_spread":0.2291334943298017,"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."}}