{"id":"W2907957654","doi":"10.1093/bioinformatics/bty1067","title":"UbiHub: a data hub for the explorers of ubiquitination pathways","year":2018,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Ubiquitin and proteasome pathways","field":"Biochemistry, Genetics and Molecular Biology","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor; Structural Genomics Consortium; University of Toronto","funders":"Eshelman Institute for Innovation, University of North Carolina at Chapel Hill; Janssen Biotech; Innovative Medicines Initiative; Novartis Pharma; Ontario Genomics Institute; Canada Foundation for Innovation; Wellcome Trust; Ontario Ministry of Research, Innovation and Science; Ontario Genomics; Fundação de Amparo à Pesquisa do Estado de São Paulo; Genome Canada; AbbVie; European Federation of Pharmaceutical Industries and Associations; Structural Genomics Consortium; Merck KGaA; Pfizer; Boehringer Ingelheim","keywords":"Ubiquitin; Proteasome; Drug discovery; Deubiquitinating enzyme; Computational biology; Protein degradation; Biology; Ubiquitin-Protein Ligases; Ubiquitin ligase; Cell biology; Bioinformatics; Biochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004736872,0.0001017132,0.00009544817,0.00002657509,0.0001252061,0.00002286073,0.0005624975,0.00008803789,0.00001679467],"category_scores_gemma":[0.0002280758,0.00007210515,0.00005225778,0.0000699544,0.0001622706,0.00001384809,0.0002623987,0.00003763147,0.00001658506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000512586,"about_ca_system_score_gemma":0.00008149034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003412706,"about_ca_topic_score_gemma":0.000009951201,"domain_scores_codex":[0.9992688,0.00001494628,0.000287569,0.0001220267,0.0001289522,0.0001776644],"domain_scores_gemma":[0.9988003,0.00004293555,0.0001755923,0.0007763457,0.0001672477,0.00003757648],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006786546,0.0002545725,0.0005330155,0.000955859,0.0004512947,6.01686e-7,0.00672989,0.00004401417,0.3408538,0.01203068,0.1311633,0.5063043],"study_design_scores_gemma":[0.0007441863,0.0007924009,0.0001413397,0.00003380745,0.00004528666,0.000008014596,0.001496701,0.0300078,0.631484,0.0003621846,0.3346668,0.0002174605],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3354945,0.001489889,0.6149598,0.001100209,0.001655828,0.003824719,0.003252374,0.0001146624,0.03810805],"genre_scores_gemma":[0.9705771,0.0001529402,0.02699634,0.0005272409,0.0006138539,0.00006577781,0.0009183117,0.00002095073,0.0001274924],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6350826,"threshold_uncertainty_score":0.2940363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07489918757800679,"score_gpt":0.2935876503722049,"score_spread":0.2186884627941981,"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."}}