{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026836,0.0003620799,0.0003009381,0.0001770511,0.0001245912,0.0002858143,0.0003165582,0.0003577786,0.001397534],"category_scores_gemma":[0.0001218887,0.0001037097,0.0002435173,0.0001244821,0.0002399203,0.0001666042,0.0001602542,0.0007627248,0.0002826012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003048036,"about_ca_system_score_gemma":0.0001778447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001810897,"about_ca_topic_score_gemma":0.0003231801,"domain_scores_codex":[0.9999042,0.00001786241,0.000004721678,0.00002478956,0.00002107497,0.00002737128],"domain_scores_gemma":[0.999957,0.00001107325,0.00001537698,0.000006239498,0.000003944351,0.000006426373],"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":[0.0004594476,0.000111743,0.0001338564,0.00007720412,0.00001877327,0.0001428546,0.00001839121,0.0004909614,0.9843644,0.002003039,0.0002998534,0.01187943],"study_design_scores_gemma":[0.00009830247,0.0008608764,0.0005951356,0.000007584277,0.00003589041,0.0004011148,0.00001415036,0.003244621,0.9857699,0.0004554804,0.008508343,0.000008678162],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9376504,0.01103516,0.03787163,0.001213151,0.0003453644,0.0001768686,0.0002987059,0.0006756312,0.01073305],"genre_scores_gemma":[0.9934717,0.001624292,0.002826996,0.00008645229,0.00002242736,0.00003329281,0.00008553876,0.00001833431,0.001830952],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001397534,"threshold_uncertainty_score":0.00467515,"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."}}