{"id":"W2108461608","doi":"10.1186/1471-2164-14-720","title":"Transcription-factor occupancy at HOT regions quantitatively predicts RNA polymerase recruitment in five human cell lines","year":2013,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"National Human Genome Research Institute; National Institutes of Health; King Abdullah University of Science and Technology","keywords":"Biology; RNA polymerase II; Promoter; Gene; Occupancy; DNA microarray; Transcription factor; Genetics; Transcription preinitiation complex; Computational biology; Gene expression; Human genome; RNA; Transcription (linguistics); Genome","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007518628,0.0002636644,0.0002218833,0.00007844375,0.0001450286,0.00004527963,0.0002721545,0.0001994027,0.00006714505],"category_scores_gemma":[0.00001814869,0.0002730608,0.0001419046,0.00007719478,0.00007329684,0.000008189935,0.0001120669,0.0001091734,0.00006539751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001198636,"about_ca_system_score_gemma":0.0001273939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002645424,"about_ca_topic_score_gemma":0.001740866,"domain_scores_codex":[0.9985883,0.00006881299,0.0004140695,0.0004612484,0.00009999511,0.0003676046],"domain_scores_gemma":[0.9991764,0.00001805507,0.0001620447,0.0004270781,0.00007440618,0.0001420024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004950888,0.0001556537,0.004036371,0.0000435512,0.00002511876,0.000002053374,0.0006619205,0.0003039018,0.9932038,0.0001245102,0.001223515,0.0001701577],"study_design_scores_gemma":[0.004681729,0.001115115,0.1279423,0.00006655249,0.00007918419,0.00002066471,0.00176278,0.0040202,0.8456174,0.0009359253,0.01229536,0.001462785],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964741,0.0009751895,0.0006990216,0.00008103414,0.0001860147,0.0008367537,0.0001938156,0.00001583608,0.000538176],"genre_scores_gemma":[0.9918407,0.0004831386,0.003759757,0.0001574121,0.0001439181,0.0001683428,0.0004518334,0.00004939121,0.002945543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1475863,"threshold_uncertainty_score":0.9999722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04445936224960439,"score_gpt":0.2744604123685211,"score_spread":0.2300010501189167,"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."}}