{"id":"W2318478693","doi":"10.1109/tcbb.2015.2453948","title":"REPA: Applying Pathway Analysis to Genome-Wide Transcription Factor Binding Data","year":2015,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Computational Biology and Bioinformatics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transcription factor; Computational biology; Genome; ENCODE; Biology; Gene; Genetics; KEGG; DNA binding site; Transcription (linguistics); Profiling (computer programming); Promoter; Gene expression; Computer science; Transcriptome","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002598127,0.000197937,0.0002174272,0.0002577192,0.0002074547,0.00005189669,0.0003610577,0.0001892677,0.00001035923],"category_scores_gemma":[0.0000435264,0.0001856252,0.00008818167,0.0003192204,0.00007176901,0.00002136274,0.0000310816,0.000126427,0.00002641132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003422732,"about_ca_system_score_gemma":0.0001097235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001002546,"about_ca_topic_score_gemma":0.00005499923,"domain_scores_codex":[0.9988509,0.00004542989,0.0004109229,0.000336925,0.0001298232,0.0002260125],"domain_scores_gemma":[0.9990083,0.00005965298,0.0001118216,0.0005127552,0.0001217547,0.0001856927],"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":[0.0006212136,0.000555253,0.01038837,0.0001586672,0.004312605,0.000006128071,0.003103273,0.8002738,0.0786642,0.0003136459,0.0005812641,0.1010216],"study_design_scores_gemma":[0.005233914,0.003418196,0.01990517,0.00006115484,0.001376219,0.0001506382,0.003588005,0.8982818,0.01472252,0.003725881,0.04661463,0.002921857],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4061727,0.00004508138,0.5922749,0.0001640979,0.0001606294,0.0001953551,0.000906179,0.00001942976,0.00006162381],"genre_scores_gemma":[0.9193218,0.00005409958,0.07703455,0.000492938,0.00005445537,0.00002349382,0.00293318,0.00001271596,0.00007278848],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5152404,"threshold_uncertainty_score":0.7569577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03872326704548541,"score_gpt":0.2810780347402999,"score_spread":0.2423547676948145,"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."}}