{"id":"W2557972923","doi":"10.1145/2975167.2985652","title":"Prediction of Cell Type Specific Transcription Factor Binding Site Occupancy","year":2016,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Transcription factor; ENCODE; DNA binding site; Logistic regression; Computer science; Motif (music); Computational biology; Transcription (linguistics); Occupancy; Sequence motif; Artificial intelligence; Biology; DNA; Machine learning; Promoter; Genetics; Gene; Gene expression","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003173635,0.0003687387,0.0006425403,0.0008469336,0.0001345336,0.0004422046,0.0003207178,0.0004961133,0.0009787505],"category_scores_gemma":[0.001068701,0.000194839,0.000440257,0.0007041358,0.0001428987,0.0003547175,0.0002150993,0.0005325911,0.0008701717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002562438,"about_ca_system_score_gemma":0.0003132794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00189203,"about_ca_topic_score_gemma":0.003622835,"domain_scores_codex":[0.999848,0.00002902658,0.000009809219,0.00005153357,0.00003485519,0.00002680956],"domain_scores_gemma":[0.9994455,0.0002530612,0.0001050691,0.00006122686,0.00009684794,0.00003826618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001179811,0.0002988544,0.2711773,0.0003127195,0.0002232297,0.0003170316,0.00006801966,0.1160435,0.3376563,0.001167697,0.003264637,0.2682909],"study_design_scores_gemma":[0.00001858177,0.0002038551,0.06768949,0.00001555351,0.00005627376,0.0002987755,0.00004250392,0.8603489,0.06663372,0.002328761,0.002323564,0.00004004276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6584905,0.002331214,0.3287128,0.0002340371,0.00005614358,0.00006041085,0.00553874,0.002645336,0.001930875],"genre_scores_gemma":[0.9292536,0.0006190957,0.06372067,0.00009343168,0.00004603425,0.00005921798,0.004891652,0.00005666669,0.001259681],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.00189203,"threshold_uncertainty_score":0.003762007,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01842271547555852,"score_gpt":0.2308693664184352,"score_spread":0.2124466509428767,"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."}}