{"id":"W2156733952","doi":"10.1093/bioinformatics/btn444","title":"Seeder: discriminative seeding DNA motif discovery","year":2008,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Centre Sève; Fonds Québécois de la Recherche sur la Nature et les Technologies; Norges Teknisk-Naturvitenskapelige Universitet","keywords":"Discriminative model; Computational biology; Computer science; DNA binding site; Promoter; Benchmark (surveying); Transcription factor; Biology; Data mining; Artificial intelligence; Genetics; Gene; Gene expression","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001816044,0.001109314,0.001239463,0.001664357,0.0005002677,0.0007949554,0.002207084,0.00103426,0.007951148],"category_scores_gemma":[0.006119965,0.0005078205,0.0006313461,0.001761419,0.0006088185,0.0009903144,0.001241688,0.001092268,0.003570756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004496685,"about_ca_system_score_gemma":0.001075736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001163738,"about_ca_topic_score_gemma":0.002091975,"domain_scores_codex":[0.9987946,0.0003250731,0.00005809382,0.0003873252,0.000368322,0.00006669802],"domain_scores_gemma":[0.9980429,0.001140713,0.0001571932,0.0002833063,0.0002652591,0.0001105882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002567053,0.0004158858,0.008619151,0.001455198,0.0002738865,0.0007296897,0.0001820655,0.1219285,0.08511163,0.02204665,0.0484628,0.7082075],"study_design_scores_gemma":[0.0002777715,0.0002146511,0.001029639,0.00003785462,0.00003616918,0.0005322936,0.00002589534,0.9248307,0.04695476,0.01583294,0.01018896,0.00003820606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03321819,0.0006280086,0.9362234,0.000160202,0.00008226524,0.0001984551,0.002570164,0.02519184,0.001727423],"genre_scores_gemma":[0.1821613,0.0002193609,0.8058501,0.0001819377,0.00005459865,0.0003399354,0.006547926,0.001028408,0.003616398],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007951148,"threshold_uncertainty_score":0.02659923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01210120642419581,"score_gpt":0.2174705794309284,"score_spread":0.2053693730067326,"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."}}