{"id":"W2965551559","doi":"10.1016/j.ccell.2019.07.003","title":"Therapeutic Targeting of RNA Splicing Catalysis through Inhibition of Protein Arginine Methylation","year":2019,"lang":"en","type":"article","venue":"Cancer Cell","topic":"Cancer-related gene regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":279,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre; Structural Genomics Consortium; Ontario Institute for Cancer Research; University of Toronto","funders":"Eshelman Institute for Innovation, University of North Carolina at Chapel Hill; Janssen Pharmaceuticals; National Institute of General Medical Sciences; National Medical Research Council; Innovative Medicines Initiative; Fondazione Umberto Veronesi; Cancer Science Institute of Singapore, National University of Singapore; National Research Foundation of Korea; Ministry of Education - Singapore; National Research Foundation Singapore; Ministero della Salute; Canada Foundation for Innovation; Merck; Ontario Ministry of Economic Development and Innovation; Cycle for Survival; Pershing Square Foundation; National Cancer Institute; College of Natural Resources, University of California Berkeley; National Heart, Lung, and Blood Institute; Edward P. Evans Foundation; Associazione Italiana per la Ricerca sul Cancro; Genome Canada; Fundação de Amparo à Pesquisa do Estado de São Paulo; AstraZeneca; European Hematology Association; Starr Foundation; National Institutes of Health; Leukemia and Lymphoma Society of Canada; Pfizer; American Glaucoma Society; Takeda Pharmaceuticals U.S.A.; Leukemia and Lymphoma Society; Amgen; Boehringer Ingelheim; National University of Singapore; Novartis Pharma; AbbVie; Henry and Marilyn Taub Foundation; Wellcome Trust; Astellas Pharma US","keywords":"Methylation; Arginine; RNA splicing; RNA; Chemistry; RNA-binding protein; Cancer research; Alternative splicing; Cell biology; Computational biology; Biochemistry; Biology; Messenger RNA; Amino acid; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001092498,0.00009230924,0.0001489023,0.00002365319,0.00001726404,0.000002982983,0.00005117358,0.0001060393,0.00009651929],"category_scores_gemma":[0.000006048337,0.00009324958,0.00007664783,0.0001293794,0.00002785413,0.000009379009,0.00002668007,0.00004428887,0.000002659235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004633391,"about_ca_system_score_gemma":0.00006606712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003875962,"about_ca_topic_score_gemma":0.00004676012,"domain_scores_codex":[0.9992944,0.00003226428,0.0002469177,0.0002052736,0.0001135754,0.0001075759],"domain_scores_gemma":[0.9993768,0.000005435914,0.0002801251,0.000207088,0.0001154357,0.00001515492],"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":[0.00005211933,0.00002020999,0.0005056254,0.0001103049,0.00003996167,3.82996e-8,0.0001555181,0.006966396,0.9891842,0.0000246894,0.00003276211,0.002908145],"study_design_scores_gemma":[0.0004294553,0.0001043927,0.0004057761,0.00005327289,0.00003990884,1.678375e-7,0.00008352554,0.0005594442,0.9969831,0.000066254,0.001177943,0.00009677697],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98851,0.006785627,0.003015887,0.00004021338,0.00009673421,0.0003156157,0.00001049025,0.000005516301,0.001219956],"genre_scores_gemma":[0.9984661,0.0002925545,0.0004668822,0.00001914245,0.0001095355,0.0000228754,0.0001524949,0.00001835442,0.0004520256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009956174,"threshold_uncertainty_score":0.3802607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007790124826974479,"score_gpt":0.2453912230885818,"score_spread":0.2376010982616074,"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."}}