{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003796818,0.0001077469,0.00009756701,0.00003712014,0.00005789916,0.00002730843,0.0001466288,0.00009825449,0.00005421011],"category_scores_gemma":[0.00001023231,0.0001174894,0.00006377455,0.00005020958,0.00003697846,0.000004386896,0.00003916009,0.00003911172,0.00002448132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001393003,"about_ca_system_score_gemma":0.00003502428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000041141,"about_ca_topic_score_gemma":0.000005992832,"domain_scores_codex":[0.9992344,0.00002477629,0.000278431,0.0001996953,0.0001312493,0.0001314686],"domain_scores_gemma":[0.999447,0.000006046252,0.0001340846,0.0002050639,0.0001599721,0.00004776148],"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":[0.000004056302,0.00006702042,0.0005772053,0.00003053205,0.00004303137,9.289865e-8,0.00009590422,0.002277125,0.9956224,0.0003232542,0.00004590691,0.0009134896],"study_design_scores_gemma":[0.0004870291,0.0001880284,0.02798186,0.00001305317,0.00004932564,0.000003476074,0.0003105025,0.08445171,0.8773762,0.008792086,0.00008000302,0.0002667468],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9544154,0.0001101053,0.04497017,0.00002884485,0.0001015719,0.0002215231,0.0000670881,0.000008882425,0.0000764458],"genre_scores_gemma":[0.9943216,0.00006230482,0.005182643,0.00004320927,0.00002339567,0.00001499847,0.0002583076,0.00001812132,0.00007543893],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1182462,"threshold_uncertainty_score":0.4791079,"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."}}