{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002257616,0.0001736747,0.0002125048,0.0000327505,0.0001485358,0.00004219272,0.0001764761,0.0001717637,0.00001692376],"category_scores_gemma":[0.0004467015,0.0001628061,0.0001432392,0.0001223858,0.00005469116,0.000008991657,0.0001169409,0.0001204061,0.00002978503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002268675,"about_ca_system_score_gemma":0.0001585298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002724251,"about_ca_topic_score_gemma":0.00002095316,"domain_scores_codex":[0.9988938,0.00008907586,0.0004227012,0.0001832292,0.0001152825,0.0002959171],"domain_scores_gemma":[0.9993355,0.00003329446,0.000233864,0.0002141355,0.00005720263,0.0001259658],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001563249,0.00008244136,0.5322097,0.0002937964,0.0001876155,0.000002948549,0.0003874792,0.3898545,0.07133842,0.0000965092,0.002450319,0.002940002],"study_design_scores_gemma":[0.0005929096,0.0002092537,0.004309547,0.000006444232,0.00004372662,0.0000067423,0.0001543177,0.9684915,0.01239613,0.00001506999,0.01348821,0.0002861544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3890408,0.0003493904,0.6097768,0.000252749,0.00007494613,0.0001288997,0.00006568719,0.00002554554,0.000285214],"genre_scores_gemma":[0.5628687,0.0001070935,0.4332546,0.002653662,0.0002745309,0.000008514164,0.0006600325,0.00003244607,0.0001404256],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.578637,"threshold_uncertainty_score":0.6639039,"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."}}