{"id":"W2131994815","doi":"10.1093/bioinformatics/btu604","title":"SignalSpider: probabilistic pattern discovery on multiple normalized ChIP-Seq signal profiles","year":2014,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Chromatin immunoprecipitation; Computational biology; Cluster analysis; DECIPHER; Computer science; ENCODE; Biology; Tiling array; Probabilistic logic; Transcription factor; Genome; Enhancer; ChIP-sequencing; DNA microarray; Gene; Genetics; Promoter; Artificial intelligence; Chromatin remodeling; Gene expression","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00290285,0.002035707,0.001239055,0.001651844,0.0006377952,0.001726002,0.003647619,0.001326706,0.01017026],"category_scores_gemma":[0.007206959,0.001160864,0.002619574,0.001530527,0.0007498622,0.001824789,0.001830763,0.002204535,0.002679146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001251925,"about_ca_system_score_gemma":0.002251486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006388481,"about_ca_topic_score_gemma":0.008966803,"domain_scores_codex":[0.9987487,0.0002831662,0.00007321313,0.0004401447,0.0003741182,0.00008073962],"domain_scores_gemma":[0.9979222,0.001320714,0.0001763631,0.0002873373,0.0002067202,0.00008657901],"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":[0.001185184,0.00035261,0.01197018,0.001307684,0.000972808,0.0008149242,0.0002279185,0.6998149,0.02393089,0.02253218,0.04356114,0.1933296],"study_design_scores_gemma":[0.00004584761,0.00002367743,0.0004358814,0.00000676046,0.0000182581,0.00005472165,0.000009753072,0.9864234,0.003910127,0.007153191,0.00189833,0.00002009594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01376223,0.0001408966,0.9262245,0.0003150738,0.00006282101,0.0001912875,0.008128377,0.05030297,0.000871798],"genre_scores_gemma":[0.1552272,0.0002516507,0.8133892,0.0004147226,0.00006966421,0.0009238619,0.02355167,0.003932542,0.002239511],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01017026,"threshold_uncertainty_score":0.03402287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007426637499481214,"score_gpt":0.2066637297803833,"score_spread":0.1992370922809021,"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."}}