{"id":"W2920967859","doi":"10.1002/gepi.22198","title":"A network approach to prioritizing susceptibility genes for genome‐wide association studies","year":2019,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Epistasis; Missing heritability problem; Biology; Computational biology; Genetic association; Genetics; Genome-wide association study; Biological network; Gene regulatory network; Gene; Centrality; Genome; Single-nucleotide polymorphism; Genotype; Mathematics; Gene expression; Statistics","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":[0.002127559,0.000970117,0.0008329378,0.006643331,0.0006648527,0.001136612,0.000780092,0.0006041946,0.002130126],"category_scores_gemma":[0.009948181,0.0003981888,0.0008219187,0.003414883,0.0004073581,0.001029706,0.000933352,0.0007666923,0.0002901802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008856825,"about_ca_system_score_gemma":0.00108134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004138387,"about_ca_topic_score_gemma":0.007595503,"domain_scores_codex":[0.9987679,0.0007204142,0.00006742087,0.0002154162,0.0001651201,0.00006363938],"domain_scores_gemma":[0.9955948,0.0031518,0.0004895826,0.000190871,0.0004102544,0.000162681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007987572,0.0003411949,0.08253615,0.0009621051,0.001610244,0.000959813,0.0005374752,0.5094582,0.03150348,0.06895629,0.005375803,0.2969605],"study_design_scores_gemma":[0.00006816843,0.000157661,0.01299333,0.0000624617,0.0002622325,0.0003150853,0.0001323638,0.9078172,0.002380173,0.07061245,0.005147896,0.00005096692],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06498976,0.001100103,0.9294994,0.0008437347,0.00005374719,0.00016981,0.000945652,0.0004993507,0.001898382],"genre_scores_gemma":[0.4953819,0.001000216,0.5000525,0.000183506,0.0001114479,0.0003699965,0.001481712,0.00009190304,0.001326868],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006643331,"threshold_uncertainty_score":0.01125175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0388964229176355,"score_gpt":0.3021281686665643,"score_spread":0.2632317457489288,"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."}}