{"id":"W2904871025","doi":"10.1093/bioinformatics/bty992","title":"Gene expression models based on transcription factor binding events confer insight into functional <i>cis</i> -regulatory variants","year":2018,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Genome British Columbia; BC Children’s Hospital Foundation; BC Children's Hospital; National Institutes of Health; Children's Hospital Foundation; Canadian Institutes of Health Research; China Scholarship Council; Genome Canada","keywords":"CTCF; Computational biology; Transcription factor; Gene; Biology; Genetics; DNA binding site; Regulation of gene expression; Regulatory sequence; Gene expression; Enhancer; Promoter","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":[0.001140817,0.001094824,0.0006175669,0.000559174,0.0002469659,0.0007353041,0.0009168159,0.0008968919,0.002954785],"category_scores_gemma":[0.004059999,0.0002984381,0.001295421,0.0006717002,0.0003938132,0.0005072595,0.0004752573,0.0012498,0.0009205732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000692415,"about_ca_system_score_gemma":0.0008181515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008462147,"about_ca_topic_score_gemma":0.007811774,"domain_scores_codex":[0.9997148,0.00009976212,0.00001313214,0.00009881514,0.00004310837,0.00003031838],"domain_scores_gemma":[0.9984536,0.001248789,0.00007179003,0.00007575374,0.000116483,0.00003357906],"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":[0.0002589705,0.00005278311,0.01288093,0.0001066809,0.0001512,0.0001004744,0.00004176472,0.963594,0.005782561,0.001985413,0.001709807,0.0133354],"study_design_scores_gemma":[0.00001111766,0.00002271023,0.001248846,0.000008952646,0.00003064584,0.00002673613,0.000008993139,0.9938056,0.001329943,0.002865102,0.0006338583,0.000007545616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3628568,0.0009379293,0.6149159,0.0008099962,0.0001145613,0.0001018204,0.01195473,0.00522901,0.003079255],"genre_scores_gemma":[0.887974,0.0003922708,0.09662364,0.0002584828,0.00004351568,0.0002202586,0.01175402,0.0005396237,0.002194149],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008462147,"threshold_uncertainty_score":0.0168258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01584725336999276,"score_gpt":0.2141445878260201,"score_spread":0.1982973344560273,"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."}}