{"id":"W2097948046","doi":"10.1371/journal.pone.0013984","title":"Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation","year":2010,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2441,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Human Genome Research Institute; National Institutes of Health; Hospital for Sick Children; Genome Canada; Ontario Genomics; Ontario Genomics Institute; Heart and Stroke Foundation of Canada","keywords":"Visualization; Computer science; Redundancy (engineering); Gene regulatory network; Set (abstract data type); Data mining; Software; Gene expression profiling; Gene; Computational biology; Biology; Genetics; Gene expression; Programming language","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":[0.00273969,0.00261368,0.001327917,0.007669183,0.001289849,0.002544977,0.002926786,0.001288731,0.02376829],"category_scores_gemma":[0.00717447,0.001216528,0.001970177,0.003486337,0.000748652,0.002267753,0.002625995,0.002714756,0.004324415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000970251,"about_ca_system_score_gemma":0.001696446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003201448,"about_ca_topic_score_gemma":0.003297737,"domain_scores_codex":[0.9987859,0.00036608,0.0001029353,0.0002341509,0.0004418211,0.00006899095],"domain_scores_gemma":[0.9968523,0.001931425,0.0002755709,0.0003129478,0.0004619167,0.0001658356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001120149,0.0003886569,0.0049018,0.005269482,0.001462784,0.001231687,0.001721763,0.06355354,0.08026471,0.05819853,0.1621201,0.6197668],"study_design_scores_gemma":[0.0004138223,0.0001579003,0.004462165,0.0004702802,0.0003785701,0.001293317,0.0002933484,0.6433873,0.0560379,0.1055743,0.1871463,0.0003847087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001947045,0.0002457869,0.9471124,0.0002632077,0.00009290158,0.0001912099,0.004028136,0.04492382,0.001195466],"genre_scores_gemma":[0.02406282,0.0004310108,0.9614951,0.000128507,0.00006686989,0.0012913,0.00542354,0.005676452,0.001424403],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02376829,"threshold_uncertainty_score":0.07951277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01547435618775175,"score_gpt":0.2675057112843436,"score_spread":0.2520313550965919,"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."}}