{"id":"W4220792293","doi":"10.1186/s40246-022-00381-4","title":"Enhancer promoter interactome and Mendelian randomization identify network of druggable vascular genes in coronary artery disease","year":2022,"lang":"en","type":"article","venue":"Human Genomics","topic":"Atherosclerosis and Cardiovascular Diseases","field":"Immunology and Microbiology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Institut universitaire de cardiologie et de pneumologie de Québec","funders":"Fonds de Recherche du Québec - Santé; Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval; Canadian Institutes of Health Research; Université Laval","keywords":"Mendelian randomization; Biology; Enhancer; Genome-wide association study; Genetics; Candidate gene; Gene; Expression quantitative trait loci; Druggability; Bioinformatics; Gene expression; Single-nucleotide polymorphism","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003683427,0.0002287262,0.0002925821,0.000966217,0.000223042,0.0002853405,0.0002239617,0.000257416,0.002274485],"category_scores_gemma":[0.001104523,0.0001587868,0.0004153102,0.0005917831,0.0002330658,0.0002343382,0.0002721427,0.0002027554,0.0001805769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002622336,"about_ca_system_score_gemma":0.0003163594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001411197,"about_ca_topic_score_gemma":0.001630574,"domain_scores_codex":[0.9995915,0.0001083928,0.00001427037,0.0001805914,0.00006227854,0.00004284723],"domain_scores_gemma":[0.9994392,0.000270867,0.000151119,0.00005008786,0.00003746045,0.00005141135],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00207727,0.000244221,0.3941802,0.0003785705,0.001181729,0.002945879,0.0002896488,0.01831659,0.4835881,0.02009316,0.001633209,0.07507136],"study_design_scores_gemma":[0.000252283,0.0004333646,0.8185636,0.00003962337,0.001376201,0.004299471,0.0001613004,0.09773458,0.03955048,0.0300613,0.007461558,0.00006627715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.961993,0.0008351672,0.0332303,0.0002433757,0.00001153764,0.00003385713,0.001748998,0.0002211726,0.001682461],"genre_scores_gemma":[0.9906281,0.0002286652,0.007174809,0.00005870765,0.000009601097,0.00003073936,0.001050319,0.00002474655,0.0007943683],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002274485,"threshold_uncertainty_score":0.007608891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01136387588478799,"score_gpt":0.2277210358659166,"score_spread":0.2163571599811286,"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."}}