{"id":"W4313052989","doi":"10.1145/3570773.3570779","title":"Prediction of Phosphorylation Sites in Amino Acid Sequences Using Convolutional Neural Networks","year":2022,"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":"University of Toronto","funders":"","keywords":"Phosphorylation; Convolutional neural network; Cascade; Computational biology; Protein phosphorylation; Computer science; Kinase; Artificial intelligence; Biochemistry; Bioinformatics; Protein kinase A; Biology; Chemistry","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":[0.0002435029,0.0007315449,0.0003746759,0.001604375,0.0002024008,0.0004657546,0.0003326258,0.0006171066,0.001429085],"category_scores_gemma":[0.001084913,0.0003635223,0.0005582229,0.0009437883,0.0002055246,0.0005009744,0.0002460674,0.0005168425,0.0006725541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006239643,"about_ca_system_score_gemma":0.0005080006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007522907,"about_ca_topic_score_gemma":0.01054186,"domain_scores_codex":[0.9998693,0.00001761968,0.00001023824,0.00004837076,0.00002863668,0.00002577858],"domain_scores_gemma":[0.9996928,0.0001208533,0.00007726278,0.0000211205,0.0000617761,0.0000262454],"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":[0.001278963,0.000394157,0.03359798,0.0004496665,0.0002568402,0.001313133,0.00005893331,0.6718821,0.09074759,0.004675152,0.005701373,0.1896441],"study_design_scores_gemma":[0.000008066442,0.00002395009,0.003439359,0.00001065222,0.00001487945,0.00006924336,0.0000058208,0.9894291,0.004842853,0.001734469,0.0004152096,0.000006480505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.722602,0.002584954,0.2643424,0.0004321304,0.0001133753,0.00008407002,0.004838583,0.002105719,0.002896822],"genre_scores_gemma":[0.9333656,0.001209902,0.05780889,0.00006234572,0.0000375646,0.00003826573,0.005324383,0.00005720149,0.002095858],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007522907,"threshold_uncertainty_score":0.01495826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01879170580720177,"score_gpt":0.2471098559786311,"score_spread":0.2283181501714293,"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."}}