{"id":"W2086893629","doi":"10.1371/journal.pgen.1003571","title":"Computational Identification of Diverse Mechanisms Underlying Transcription Factor-DNA Occupancy","year":2013,"lang":"en","type":"article","venue":"PLoS Genetics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Human Genome Research Institute; Lawrence Berkeley National Laboratory; National Institute of General Medical Sciences; Centre National de la Recherche Scientifique; European Molecular Biology Laboratory; York University; U.S. Department of Energy; Division of Emerging Frontiers in Research and Innovation; National Institutes of Health; National Science Foundation","keywords":"Biology; Transcription factor; Computational biology; Chromatin; DNA binding site; Occupancy; Chromatin immunoprecipitation; Binding site; DNA microarray; Genetics; DNA; Promoter; Gene expression; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002090003,0.000660994,0.001140217,0.0007090376,0.0004592326,0.0009360683,0.001549198,0.001239094,0.001193363],"category_scores_gemma":[0.005483894,0.0007111711,0.001011512,0.0004883789,0.0006905793,0.0007542565,0.0006367593,0.0008721511,0.0001644088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001074364,"about_ca_system_score_gemma":0.001782255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009396771,"about_ca_topic_score_gemma":0.009439682,"domain_scores_codex":[0.999632,0.0001423169,0.00001880195,0.00009820807,0.00004972825,0.00005891554],"domain_scores_gemma":[0.9968981,0.002648567,0.0001322598,0.00009413081,0.000120101,0.0001068088],"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":[0.00004937336,0.00003033444,0.002544409,0.00001686517,0.00002518485,0.00002624443,0.000009903029,0.9947837,0.0003860854,0.0004903699,0.00006885829,0.001568603],"study_design_scores_gemma":[0.000002953459,0.000004102818,0.0001857305,4.995139e-7,0.00000186763,0.000001933039,0.000001705236,0.9995278,0.00005768053,0.0002064239,0.000008403131,9.349527e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9362555,0.0001972522,0.06122216,0.0002363515,0.00001349262,0.00003977351,0.000412868,0.0003772073,0.001245298],"genre_scores_gemma":[0.9885639,0.00005221501,0.0101734,0.00006684237,0.000008456193,0.00007717481,0.0006100145,0.00004201399,0.0004060128],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009396771,"threshold_uncertainty_score":0.01868415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02785271964482088,"score_gpt":0.2458969456905977,"score_spread":0.2180442260457768,"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."}}