{"id":"W2171898201","doi":"10.1186/1471-2105-15-s6-s6","title":"Functional and genetic analysis of the colon cancer network","year":2014,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"Queen's University; Queen's University Belfast","keywords":"Gene; DNA microarray; Computational biology; Biology; Gene regulatory network; Interaction network; Genome; Complex disease; Cancer; Genetics; Network analysis; Set (abstract data type); Biological network; Functional analysis; Computer science; Gene expression","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":[0.000330456,0.0003152869,0.0001843239,0.00154216,0.0003854412,0.0003422101,0.0003045787,0.0002402055,0.002068504],"category_scores_gemma":[0.001907772,0.0001099693,0.0004125666,0.001417897,0.0002533754,0.0002747353,0.0002741137,0.0002588259,0.0002080691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006405883,"about_ca_system_score_gemma":0.0005165314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007975369,"about_ca_topic_score_gemma":0.008182556,"domain_scores_codex":[0.9997528,0.00007706548,0.000006699663,0.00007452587,0.00006417844,0.00002473448],"domain_scores_gemma":[0.9992571,0.000395575,0.0001119295,0.00005830382,0.000134882,0.00004217254],"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":[0.0006320761,0.0001614557,0.1156713,0.0006577056,0.0004265161,0.001437159,0.0003197158,0.6841135,0.07107041,0.03635965,0.004697047,0.08445346],"study_design_scores_gemma":[0.00002228896,0.00007766015,0.07648097,0.00003093217,0.0001227513,0.000539273,0.0001520644,0.8831899,0.008457639,0.02298698,0.007919399,0.0000201514],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8492955,0.0008857549,0.1317424,0.0007800305,0.00002356373,0.00007347698,0.01066399,0.0005963845,0.005938898],"genre_scores_gemma":[0.9395205,0.00037276,0.05018566,0.0000438792,0.00001489446,0.0000669869,0.00827748,0.00004342589,0.001474347],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007975369,"threshold_uncertainty_score":0.01585788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009058436959456604,"score_gpt":0.2132412179480606,"score_spread":0.204182780988604,"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."}}