{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007211756,0.0001309554,0.0002024897,0.0001611509,0.0002781945,0.0000728876,0.0003749219,0.0001184798,0.00007761325],"category_scores_gemma":[0.0002285405,0.0001172597,0.00005768699,0.0002969833,0.0003634206,0.000008796869,0.0004082686,0.0003467464,0.00001233305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002771048,"about_ca_system_score_gemma":0.0001431426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001111316,"about_ca_topic_score_gemma":0.0000189246,"domain_scores_codex":[0.9980826,0.0001685829,0.000236352,0.0004159715,0.0005383673,0.0005581654],"domain_scores_gemma":[0.9992486,0.00002620723,0.00005398003,0.0002248479,0.00018967,0.000256674],"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":[0.00007689257,0.000008953119,0.0007634098,0.0001467533,0.0000413897,0.00001517237,0.0004660919,0.0000114667,0.9972244,0.0001619832,0.00008134816,0.001002168],"study_design_scores_gemma":[0.0003421495,0.0009790752,0.0007794965,0.0000282998,0.000003157244,0.000005179214,0.002089894,0.00008030352,0.9934915,0.00009732666,0.001953184,0.0001504402],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966218,0.0009959401,0.0001176316,0.000513324,0.00001608226,0.0004012103,0.0000505542,0.000009798177,0.001273676],"genre_scores_gemma":[0.9971352,0.0004629684,0.00076438,0.00001699589,0.0003746653,0.00001928542,0.00006074319,0.00002413041,0.001141624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003732876,"threshold_uncertainty_score":0.4781713,"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."}}