{"id":"W3008598131","doi":"10.1038/s41467-020-14337-6","title":"RADICL-seq identifies general and cell type–specific principles of genome-wide RNA-chromatin interactions","year":2020,"lang":"en","type":"article","venue":"Nature Communications","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":166,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Occupational Cancer Research Centre; McGill University Health Centre","funders":"RIKEN; Medical Research Council; Ministry of Education, Culture, Sports, Science and Technology; Russian Science Foundation; Ministero dell’Istruzione, dell’Università e della Ricerca; Karolinska Institutet; European Commission; King Abdullah University of Science and Technology; Wellcome Trust; Francis Crick Institute; Vetenskapsrådet; Cancer Research UK","keywords":"Chromatin; ChIA-PET; Genome; Biology; RNA; ENCODE; Computational biology; Genetics; Transcription (linguistics); Gene; Chromosome conformation capture; Long non-coding RNA; Chromatin remodeling; Gene expression; Enhancer","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":[0.0005153445,0.0003425363,0.0005037452,0.0006132486,0.0003613309,0.00089641,0.0005231468,0.0004558229,0.001769542],"category_scores_gemma":[0.0005324437,0.0003918252,0.0004769687,0.000450039,0.0003955345,0.0003962621,0.0006575226,0.0007237294,0.00103946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003551251,"about_ca_system_score_gemma":0.0003682282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001062412,"about_ca_topic_score_gemma":0.005078463,"domain_scores_codex":[0.9994837,0.00003637039,0.00001634883,0.0002848907,0.0001267396,0.00005193552],"domain_scores_gemma":[0.999588,0.0001473546,0.00008205104,0.00006303251,0.0000794655,0.0000401425],"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":[0.00005030084,0.0000114388,0.003468448,0.0001137997,0.0000281582,0.0000511973,0.00005609431,0.0005271679,0.987189,0.0006682046,0.0003582096,0.007478054],"study_design_scores_gemma":[0.00002528334,0.0001473008,0.08773184,0.0000461781,0.00009447682,0.0006997162,0.0002051336,0.02116148,0.8585823,0.002266062,0.02895651,0.00008386547],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.649585,0.004502389,0.3127072,0.0004575304,0.0001752669,0.0001592503,0.01153777,0.003927524,0.01694809],"genre_scores_gemma":[0.8655615,0.001700468,0.1109779,0.001169019,0.00007646775,0.000184614,0.01174859,0.0009171155,0.007664282],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001769542,"threshold_uncertainty_score":0.005919695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01797216490246847,"score_gpt":0.2590328680174855,"score_spread":0.241060703115017,"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."}}