{"id":"W3168819073","doi":"10.1093/nar/gkab442","title":"eSkip-Finder: a machine learning-based web application and database to identify the optimal sequences of antisense oligonucleotides for exon skipping","year":2021,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Muscular Dystrophy Canada; Alberta Innovates; Alberta Innovates - Health Solutions; Women and Children's Health Research Institute; Children's Health Research Institute","keywords":"Exon skipping; Exon; RNA splicing; Computational biology; Bioinformatics; Biology; Intron; splice; Alternative splicing; Computer science; Genetics; Gene; RNA","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001905517,0.004959326,0.003486583,0.00656327,0.0009090664,0.002316742,0.005334781,0.003390729,0.03408956],"category_scores_gemma":[0.007256825,0.001646213,0.002129408,0.004685515,0.0005845064,0.003290021,0.002834002,0.002375177,0.04486874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001256043,"about_ca_system_score_gemma":0.002705605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001698856,"about_ca_topic_score_gemma":0.002458814,"domain_scores_codex":[0.9989165,0.0001030976,0.0001541054,0.0002967166,0.0004234251,0.0001061147],"domain_scores_gemma":[0.997375,0.001315845,0.0004966809,0.000275894,0.0003019217,0.0002347546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002733059,0.0006406835,0.006153368,0.01086296,0.0006538332,0.001418,0.0002481102,0.008754814,0.03139058,0.008816522,0.762229,0.1660989],"study_design_scores_gemma":[0.001958753,0.0006186104,0.008951989,0.001314582,0.0004761603,0.002171684,0.0002380808,0.07546088,0.08789127,0.03386494,0.7865088,0.0005442625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.01356132,0.007155166,0.1035895,0.0008365391,0.0005121225,0.0005632814,0.4232807,0.4358332,0.01466826],"genre_scores_gemma":[0.03049099,0.004428624,0.1953479,0.001056746,0.0001499452,0.001920483,0.7311246,0.02693244,0.008548298],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.03408956,"threshold_uncertainty_score":0.114041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04389906512644096,"score_gpt":0.3618154180910102,"score_spread":0.3179163529645692,"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."}}