{"id":"W2950655801","doi":"10.1093/bioinformatics/bty717","title":"C3D: a tool to predict 3D genomic interactions between cis-regulatory elements","year":2018,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; Ontario Institute for Cancer Research; University of Waterloo; University Health Network","funders":"Canadian Institutes of Health Research","keywords":"Chromatin; Source code; Computational biology; Computer science; Promoter; License; MIT License; Genome; DNA; R package; Gene; Biology; Data mining; Genetics; Programming language; Gene expression; Operating system","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":[0.00185377,0.004404736,0.002336226,0.002732913,0.00170249,0.00257577,0.00497881,0.00200852,0.03919894],"category_scores_gemma":[0.006652438,0.001939343,0.003853648,0.00211675,0.000897127,0.001469055,0.003119377,0.003045982,0.01469812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001148835,"about_ca_system_score_gemma":0.002986734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01166194,"about_ca_topic_score_gemma":0.01676572,"domain_scores_codex":[0.9989722,0.0001604622,0.00005710718,0.0003575222,0.0003534544,0.00009927475],"domain_scores_gemma":[0.9980887,0.001260068,0.0001189998,0.0002118433,0.0001846878,0.0001357701],"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":[0.001748334,0.0004691547,0.02656946,0.006114119,0.001901407,0.0015738,0.0009236219,0.142804,0.04204022,0.02494285,0.6109722,0.139941],"study_design_scores_gemma":[0.0007275824,0.0002091596,0.007599463,0.0003539679,0.0004542426,0.001119155,0.0002249822,0.689212,0.03968219,0.03261046,0.2274803,0.0003265702],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02229762,0.001097332,0.4778722,0.0005690271,0.0003637757,0.0004583398,0.1698088,0.3205184,0.007014462],"genre_scores_gemma":[0.1000214,0.001192571,0.5409037,0.0008105538,0.0001098383,0.002575171,0.2903402,0.0587668,0.005279731],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03919894,"threshold_uncertainty_score":0.1311335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008380410046805961,"score_gpt":0.2422155484755282,"score_spread":0.2338351384287222,"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."}}