{"id":"W2149216452","doi":"10.1074/jbc.m112.361790","title":"Retinoic Acid Receptors Recognize the Mouse Genome through Binding Elements with Diverse Spacing and Topology","year":2012,"lang":"en","type":"article","venue":"Journal of Biological Chemistry","topic":"Retinoids in leukemia and cellular processes","field":"Biochemistry, Genetics and Molecular Biology","cited_by":162,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institut National Du Cancer; Université de Strasbourg; Institute of Genetics; Institut National de la Santé et de la Recherche Médicale; Agence Nationale de la Recherche; Centre National de la Recherche Scientifique; European Commission","keywords":"Retinoid X receptor; Retinoic acid; Genome; Biology; Retinoid X receptor alpha; Genetics; Retinoid; Inverted repeat; Retinoic acid receptor; Receptor; Gene; Response element; Cell biology; Molecular biology; Computational biology; Nuclear receptor; Gene expression; Transcription factor; Promoter","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001156293,0.0003115605,0.0001456995,0.0004880476,0.0001336168,0.0002940707,0.0002143197,0.0001725994,0.002731692],"category_scores_gemma":[0.00009764107,0.0001697071,0.0001539031,0.0002547296,0.000163655,0.0001636834,0.0002118508,0.0002839383,0.001347892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001501594,"about_ca_system_score_gemma":0.0001070611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003528148,"about_ca_topic_score_gemma":0.0009297919,"domain_scores_codex":[0.999822,0.00004078926,0.00001002973,0.00005079178,0.00004652433,0.00003003897],"domain_scores_gemma":[0.9999238,0.0000102304,0.00002927611,0.00001238535,0.000006730012,0.00001750156],"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":[0.00005637132,0.00000361343,0.0005610615,0.00001296401,0.000003574842,0.0000156496,0.000008341169,0.00002068026,0.9969,0.0001602993,0.00003104113,0.002226428],"study_design_scores_gemma":[0.00003863209,0.00039524,0.03883955,0.00002371526,0.00004403701,0.001133346,0.00007983013,0.0006604724,0.9378639,0.0005140542,0.02039457,0.00001271379],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9743034,0.00428192,0.01252713,0.0001134581,0.00002378705,0.00002729088,0.001387946,0.0003944594,0.00694051],"genre_scores_gemma":[0.9731838,0.002559652,0.01364932,0.0001249012,0.00001299716,0.00004037103,0.002054058,0.00006196016,0.008313019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002731692,"threshold_uncertainty_score":0.009138405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02128399670445929,"score_gpt":0.2505865038465642,"score_spread":0.2293025071421049,"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."}}