{"id":"W4296780664","doi":"10.1093/bioinformatics/btac478","title":"GNN-SubNet: disease subnetwork detection with explainable graph neural networks","year":2022,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Austrian Science Fund; European Commission","keywords":"Subnetwork; Subnet; Interpretability; Computer science; Python (programming language); Graph; Machine learning; Artificial intelligence; Data mining; Theoretical computer science; Computer network","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007918541,0.001459482,0.0006519479,0.001733695,0.0003700737,0.0008955051,0.001721899,0.001219892,0.01017326],"category_scores_gemma":[0.004438291,0.000501733,0.001281938,0.0007305556,0.0004168698,0.0009971339,0.001454695,0.001224648,0.002334495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009179084,"about_ca_system_score_gemma":0.001223609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007035447,"about_ca_topic_score_gemma":0.01210344,"domain_scores_codex":[0.9997348,0.00007014718,0.00001491588,0.00009828994,0.000052953,0.00002886714],"domain_scores_gemma":[0.9993818,0.0003249033,0.00006405955,0.0001119384,0.0000712135,0.00004604779],"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":[0.000589442,0.0002498238,0.01701956,0.001249408,0.0007341512,0.0008717372,0.0002485399,0.4944516,0.007748808,0.02463655,0.1168531,0.3353472],"study_design_scores_gemma":[0.00004366074,0.00002641136,0.0009250205,0.00004195121,0.00004201187,0.0001297384,0.00001437588,0.9653618,0.002014603,0.02401234,0.007370435,0.00001769389],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03263903,0.0008560882,0.8737591,0.001537959,0.0002836392,0.0002759311,0.02174327,0.06519765,0.003707375],"genre_scores_gemma":[0.3789192,0.0008233497,0.555931,0.000868445,0.0001787946,0.0007700063,0.05228948,0.003483922,0.00673589],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01017326,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005619933380862117,"score_gpt":0.188813731602062,"score_spread":0.1831937982211999,"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."}}