{"id":"W3138998566","doi":"10.3389/fcell.2021.626821","title":"ActiveDriverDB: Interpreting Genetic Variation in Human and Cancer Genomes Using Post-translational Modification Sites and Signaling Networks (2021 Update)","year":2021,"lang":"en","type":"article","venue":"Frontiers in Cell and Developmental Biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Université Laval; University of Toronto; Ontario Institute for Cancer Research","funders":"Ontario Institute for Cancer Research; Canadian Institutes of Health Research; Government of Ontario; Cancer Research Society","keywords":"Biology; Computational biology; Genetics; Genetic variation; Phosphoproteomics; Genome; Population; Genomics; Human genome; Human genetic variation; Gene; Phosphorylation; Protein kinase A; Protein phosphorylation","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":[0.002602178,0.002457375,0.00202067,0.00529672,0.0007838036,0.003762483,0.002986823,0.00175975,0.01616647],"category_scores_gemma":[0.009167487,0.001361093,0.00193208,0.00432706,0.0003508456,0.001764226,0.003790544,0.001571533,0.01009414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009206964,"about_ca_system_score_gemma":0.001669787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01171114,"about_ca_topic_score_gemma":0.01918554,"domain_scores_codex":[0.9984204,0.0002811707,0.0002290659,0.000545517,0.0003788558,0.0001449806],"domain_scores_gemma":[0.9970567,0.001079596,0.000399658,0.000635853,0.0004875092,0.0003406363],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001683936,0.0001622516,0.04216896,0.005521733,0.001943629,0.0009260983,0.000525751,0.005004886,0.01201218,0.002871815,0.8078082,0.1193705],"study_design_scores_gemma":[0.001030386,0.0002453927,0.06634046,0.001062795,0.001117618,0.001824701,0.0003194325,0.01747676,0.01398352,0.01300539,0.8833019,0.000291589],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.01017174,0.003667039,0.01195632,0.000673121,0.0002228279,0.0001428273,0.9451347,0.02529377,0.002737707],"genre_scores_gemma":[0.01606698,0.001552851,0.02540351,0.000612553,0.00008662321,0.0003845989,0.9527394,0.002105444,0.00104805],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01616647,"threshold_uncertainty_score":0.05408227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007832459401717985,"score_gpt":0.2292861646587754,"score_spread":0.2214537052570574,"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."}}