{"id":"W2140996283","doi":"10.1371/journal.pbio.1000218","title":"Bayesian Modeling of the Yeast SH3 Domain Interactome Predicts Spatiotemporal Dynamics of Endocytosis Proteins","year":2009,"lang":"en","type":"article","venue":"PLoS Biology","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":200,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institute of General Medical Sciences; Canadian Institutes of Health Research; Associazione Italiana per la Ricerca sul Cancro; Deutsche Forschungsgemeinschaft; National Science Foundation; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Interactome; Biology; Endocytosis; SH3 domain; Yeast; Computational biology; Domain (mathematical analysis); Protein–protein interaction; Genetics; Gene; Signal transduction; Proto-oncogene tyrosine-protein kinase Src","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":[0.001198575,0.0003611832,0.0004472613,0.0008055476,0.0003483994,0.0006329501,0.000597022,0.0006488368,0.0007539881],"category_scores_gemma":[0.00301387,0.0005510046,0.000638784,0.0003406824,0.0004552894,0.0006997845,0.0004239504,0.0005330498,0.000157264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009969486,"about_ca_system_score_gemma":0.0006611437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01442542,"about_ca_topic_score_gemma":0.01156837,"domain_scores_codex":[0.9998299,0.00005984415,0.000007480138,0.00004407349,0.00002837872,0.00003031482],"domain_scores_gemma":[0.9989691,0.0007356865,0.0001235415,0.0000376076,0.00007120549,0.00006293775],"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":[0.0001348827,0.00003021024,0.009480935,0.00001597618,0.0000544834,0.00004886898,0.00002429738,0.9809831,0.002018277,0.003489541,0.0002961159,0.003423346],"study_design_scores_gemma":[0.000003627912,0.000002590641,0.0007919254,8.293146e-7,0.00000217614,0.000004341955,0.000001916127,0.9981462,0.00008311619,0.0009381691,0.0000233316,0.000001759514],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8975985,0.0002207307,0.1003046,0.0003755138,0.000006693838,0.00001889589,0.0003400023,0.0001787859,0.0009562469],"genre_scores_gemma":[0.9921718,0.00009354321,0.006907911,0.00002668838,0.000007311779,0.00001829329,0.0003184294,0.00001850751,0.0004374881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01442542,"threshold_uncertainty_score":0.02868295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00780076212106825,"score_gpt":0.2289696079209735,"score_spread":0.2211688457999053,"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."}}