{"id":"W2799961961","doi":"10.1101/317909","title":"Binding specificities of human RNA binding proteins towards structured and linear RNA sequences","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Knut och Alice Wallenbergs Stiftelse; Vetenskapsrådet; Karolinska Institutet; Mayo Clinic","keywords":"RNA-binding protein; RNA; Riboswitch; RNA recognition motif; RNA splicing; Biology; Computational biology; Systematic evolution of ligands by exponential enrichment; RNase P; Binding site; Structural motif; Genetics; Sequence motif; 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":[0.0001809149,0.0003157399,0.000238714,0.0003525077,0.000124597,0.0002329532,0.0001800112,0.0002548353,0.001666221],"category_scores_gemma":[0.0002542844,0.0001476407,0.0002946676,0.0003158965,0.0001463757,0.00007941209,0.0002341302,0.0001984697,0.0007635109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002267825,"about_ca_system_score_gemma":0.00008927583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009805219,"about_ca_topic_score_gemma":0.001132612,"domain_scores_codex":[0.9998313,0.00003106603,0.000008999682,0.0000493335,0.00004329572,0.00003596074],"domain_scores_gemma":[0.9998747,0.00005206808,0.00001857767,0.00001028211,0.00001829497,0.00002605015],"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":[0.0001684734,0.00001646677,0.00176286,0.00004502827,0.00002153418,0.00003979146,0.00001751919,0.0003222268,0.9954211,0.00005854412,0.00007670509,0.002049751],"study_design_scores_gemma":[0.00001880066,0.0002446793,0.02749809,0.000008451267,0.00003554942,0.0005602328,0.00005336518,0.004639165,0.9644461,0.0001076598,0.002373982,0.00001379739],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954058,0.0009442407,0.002299812,0.00003054087,0.000004274571,0.00001473126,0.0004885845,0.00004396929,0.0007680731],"genre_scores_gemma":[0.9958365,0.0001713346,0.002250622,0.00004996141,0.000002333555,0.00001255129,0.001049336,0.00001228627,0.0006149958],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001666221,"threshold_uncertainty_score":0.005574048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02302347841083351,"score_gpt":0.2659450245001009,"score_spread":0.2429215460892674,"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."}}