{"id":"W3136190116","doi":"10.1016/j.mcpro.2021.100075","title":"Mapping Isoform Abundance and Interactome of the Endogenous TMPRSS2-ERG Fusion Protein by Orthogonal Immunoprecipitation–Mass Spectrometry Assays","year":2021,"lang":"en","type":"article","venue":"Molecular & Cellular Proteomics","topic":"Prostate Cancer Treatment and Research","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Calgary Laboratory Services; University of Calgary; University of Alberta","funders":"China Scholarship Council; Mitacs; National Natural Science Foundation of China; Prostate Cancer Canada","keywords":"Interactome; TMPRSS2; Fusion protein; Gene isoform; Prostate cancer; Erg; Molecular biology; Biology; Immunoprecipitation; Fusion gene; Computational biology; Chemistry; Cancer research; Gene; Cancer; Genetics; Biochemistry; Recombinant DNA; Medicine; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003260691,0.0004217926,0.0002737574,0.0008727687,0.0002620541,0.0004346063,0.0002491791,0.0002180572,0.0009753783],"category_scores_gemma":[0.000228933,0.0001907588,0.0002737154,0.0005545404,0.000250275,0.0001822833,0.0003140284,0.0003403063,0.0004064243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003193339,"about_ca_system_score_gemma":0.0002047857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007738549,"about_ca_topic_score_gemma":0.001230498,"domain_scores_codex":[0.9996969,0.00003899547,0.00002320042,0.0000894031,0.0001013382,0.00005020916],"domain_scores_gemma":[0.9998604,0.00003631269,0.00003872321,0.00001450807,0.00003143462,0.00001854299],"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":[0.00006376711,0.00001236879,0.0009443683,0.00002862299,0.00001138447,0.00002888977,0.00001651898,0.00004443111,0.9978733,0.00006860335,0.00003574743,0.0008719734],"study_design_scores_gemma":[0.00001026936,0.0001079299,0.0435879,0.000006068689,0.00005126225,0.0005433731,0.00007320316,0.004679827,0.9481321,0.0001063691,0.00268953,0.00001214507],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9731653,0.001322412,0.02174121,0.00009400817,0.00001762923,0.00005345911,0.001688559,0.0002416948,0.001675627],"genre_scores_gemma":[0.9598832,0.001596668,0.03050607,0.0001316486,0.00002606709,0.0001659523,0.003840061,0.0001143033,0.003736063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009753783,"threshold_uncertainty_score":0.003262937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01269222759565706,"score_gpt":0.2358349677718788,"score_spread":0.2231427401762217,"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."}}