{"id":"W3043851516","doi":"10.1101/gr.258848.119","title":"Binding specificities of human RNA-binding proteins toward structured and linear RNA sequences","year":2020,"lang":"en","type":"article","venue":"Genome Research","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":125,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Medical Research Council; National Cancer Institute; Cancer Research UK; Vetenskapsrådet; Mayo Clinic; Karolinska Institutet; Knut och Alice Wallenbergs Stiftelse","keywords":"RNA-binding protein; RNA; Biology; Riboswitch; RNA recognition motif; RNA splicing; Computational biology; RNase P; Systematic evolution of ligands by exponential enrichment; Genetics; Structural motif; Binding site; Nucleic acid structure; Non-coding RNA; Cell biology; Gene; Biochemistry","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":[0.0002067347,0.0003143417,0.000288338,0.0002643308,0.0001217913,0.0002463747,0.0001934591,0.0002266486,0.001060031],"category_scores_gemma":[0.0002836596,0.0001503566,0.0002447596,0.0003421013,0.0001507865,0.00008781462,0.0002057408,0.0002209198,0.0005832229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002292043,"about_ca_system_score_gemma":0.0001166085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001095815,"about_ca_topic_score_gemma":0.001550744,"domain_scores_codex":[0.9998053,0.00003582521,0.00001161675,0.00005416719,0.0000573668,0.00003589067],"domain_scores_gemma":[0.999897,0.00004404674,0.00001474662,0.00001110718,0.00001429771,0.00001879577],"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":[0.0001897439,0.00002129449,0.002824676,0.0000594956,0.00002489734,0.00004631985,0.0000262854,0.0005723397,0.9911271,0.00008514017,0.0001090344,0.004913626],"study_design_scores_gemma":[0.00002374449,0.0002166013,0.03503155,0.000008943366,0.00004761063,0.0007690006,0.00005441765,0.004586232,0.9553167,0.0001424979,0.003783145,0.00001962336],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950044,0.001412342,0.002222031,0.00003534174,0.000002882841,0.0000128252,0.0004999332,0.00005559219,0.0007547881],"genre_scores_gemma":[0.9941848,0.0003996878,0.003250485,0.00005724016,0.000002540262,0.00001429636,0.001414181,0.00001555614,0.0006613698],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001095815,"threshold_uncertainty_score":0.003546178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1141593165035827,"score_gpt":0.3660457035000916,"score_spread":0.2518863869965089,"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."}}