{"id":"W4412626392","doi":"10.1093/bioadv/vbaf178","title":"Gene-set enrichment analysis and visualization on the web using EnrichmentMap:RNASeq","year":2024,"lang":"en","type":"article","venue":"Bioinformatics Advances","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Princess Margaret Cancer Centre; University Health Network; University of Toronto","funders":"National Institutes of Health","keywords":"Visualization; Computational biology; Set (abstract data type); Biology; Computer science; Genetics; World Wide Web; Data mining; Programming language","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":[0.001727271,0.002190591,0.001348328,0.004820586,0.001091548,0.002027588,0.001907937,0.0009859293,0.1095631],"category_scores_gemma":[0.003402991,0.0009737557,0.001465388,0.002717142,0.0003971329,0.001599872,0.002266999,0.002233793,0.04142509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004682281,"about_ca_system_score_gemma":0.001211059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002156377,"about_ca_topic_score_gemma":0.003901524,"domain_scores_codex":[0.9986915,0.000140388,0.00008015317,0.0003538616,0.0006009499,0.0001331112],"domain_scores_gemma":[0.9983707,0.0007364229,0.00009920646,0.0002090073,0.0004335289,0.0001510687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009109913,0.0002522805,0.003438945,0.003198251,0.0005587924,0.0008226699,0.0005074329,0.00214392,0.07282641,0.004661574,0.7567441,0.1539346],"study_design_scores_gemma":[0.0005803027,0.0001902049,0.01596666,0.0006441346,0.000267451,0.001427207,0.0002759143,0.04014242,0.1922854,0.03015869,0.7175361,0.0005254837],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.01212769,0.001164394,0.2555358,0.001099264,0.000825691,0.000517648,0.1829243,0.5273463,0.01845895],"genre_scores_gemma":[0.0643707,0.001457247,0.5211263,0.002156588,0.0004641794,0.003829487,0.2800864,0.09258807,0.03392101],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1095631,"threshold_uncertainty_score":0.3665252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01282611854482546,"score_gpt":0.278922961500048,"score_spread":0.2660968429552225,"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."}}