{"id":"W3012879287","doi":"10.1186/s12859-020-3368-2","title":"GenEpi: gene-based epistasis discovery using machine learning","year":2020,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, San Diego; Genentech; National Institutes of Health; H. Lundbeck A/S; Servier; Nanjing University of Aeronautics and Astronautics; National Natural Science Foundation of China; Eisai; U.S. National Library of Medicine; IXICO; Northern California Institute for Research and Education; Ministry of Science and Technology, Taiwan; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Scheme for Promotion of Academic and Research Collaboration; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Foundation for the National Institutes of Health; Alzheimer's Disease Neuroimaging Initiative; National Center for Advancing Translational Sciences; Meso Scale Diagnostics; Alzheimer's Association; National Science Foundation","keywords":"Epistasis; Genome-wide association study; Computational biology; Computer science; Machine learning; Biology; Artificial intelligence; Genetics; Gene; Single-nucleotide polymorphism; Genotype","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":[0.001878081,0.001573344,0.001454926,0.001202421,0.0005008426,0.0009105678,0.002360503,0.0009981628,0.006806249],"category_scores_gemma":[0.00653314,0.0006945606,0.002143125,0.001007003,0.0005252005,0.0007368044,0.001227372,0.001900524,0.001794294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004558783,"about_ca_system_score_gemma":0.001800989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002504042,"about_ca_topic_score_gemma":0.003034179,"domain_scores_codex":[0.9993025,0.0003171944,0.00002958612,0.0001601967,0.0001436444,0.00004690886],"domain_scores_gemma":[0.9979441,0.001611383,0.0001240258,0.0001503597,0.0001021287,0.00006807847],"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":[0.001130548,0.0006759527,0.02217507,0.001593264,0.002064394,0.001123913,0.0003985486,0.517149,0.01337421,0.04458896,0.06577872,0.3299474],"study_design_scores_gemma":[0.00009877297,0.00005438166,0.0007245863,0.0000134017,0.00006857023,0.00009362648,0.000008350514,0.9805818,0.001282736,0.01318042,0.003872222,0.00002108971],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01138458,0.0002932029,0.9532869,0.0003172638,0.00007187959,0.0001522325,0.002378766,0.03111577,0.0009994624],"genre_scores_gemma":[0.1388542,0.0003754461,0.8493971,0.0004021309,0.00007090415,0.001221217,0.005410569,0.00246688,0.001801533],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006806249,"threshold_uncertainty_score":0.02276921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0393174571091678,"score_gpt":0.263435359177519,"score_spread":0.2241179020683512,"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."}}