{"id":"W2005546833","doi":"10.1371/journal.pcbi.0040005","title":"In Silico Detection of Sequence Variations Modifying Transcriptional Regulation","year":2008,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research; Child and Family Research Institute; Princess Margaret Cancer Centre; University of British Columbia","funders":"Canadian Institutes of Health Research; Vetenskapsrådet; Stockholms Läns Landsting; University of Toronto; Michael Smith Health Research BC","keywords":"In silico; Biology; Genetics; Computational biology; DNA binding site; Gene; Enhancer; Genetic variation; Regulatory sequence; Transcription factor; Single-nucleotide polymorphism; Bioinformatics; Promoter; Gene expression; Genotype","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":[0.001196248,0.0006813464,0.001004786,0.0006383716,0.0003060633,0.0005616005,0.0006895281,0.0007747551,0.001719702],"category_scores_gemma":[0.002244292,0.0004277052,0.001066058,0.0004550315,0.0002871252,0.0002310055,0.000315277,0.000523735,0.0004459524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004007394,"about_ca_system_score_gemma":0.0006807515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001021342,"about_ca_topic_score_gemma":0.00169601,"domain_scores_codex":[0.99944,0.0002583716,0.00003137459,0.0001360026,0.00008816476,0.00004612937],"domain_scores_gemma":[0.9983436,0.001333876,0.0001100466,0.0001020518,0.00007430586,0.00003607012],"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":[0.001927717,0.0006254681,0.03039603,0.000846909,0.0006289931,0.0007284698,0.0002916218,0.5665157,0.352057,0.0065904,0.00234486,0.03704677],"study_design_scores_gemma":[0.00008239994,0.0002014545,0.00368081,0.000009429823,0.0001365881,0.0001531991,0.0000252868,0.941467,0.05028606,0.00186279,0.002071154,0.00002384249],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7313811,0.0004074638,0.2562749,0.0002263839,0.00007739021,0.0001333503,0.002999873,0.005852449,0.002647052],"genre_scores_gemma":[0.823634,0.0003067382,0.1685379,0.0001421774,0.00002180968,0.0002743831,0.005523518,0.0004989262,0.001060514],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001719702,"threshold_uncertainty_score":0.006326437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04158741154063465,"score_gpt":0.2615315130370233,"score_spread":0.2199441014963886,"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."}}