{"id":"W2336308079","doi":"10.1101/pdb.prot088880","title":"Use of the BioGRID Database for Analysis of Yeast Protein and Genetic Interactions","year":2016,"lang":"en","type":"article","venue":"Cold Spring Harbor Protocols","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Sinai Hospital; Lunenfeld-Tanenbaum Research Institute; Université de Montréal; Institute for Research in Immunology and Cancer","funders":"National Center for Research Resources; Canadian Institutes of Health Research; Biotechnology and Biological Sciences Research Council; Directorate for Biological Sciences; National Institutes of Health","keywords":"Schizosaccharomyces pombe; Budding yeast; Yeast; Candida albicans; Saccharomyces cerevisiae; Biology; Schizosaccharomyces; Computational biology; Database; Bioinformatics; Genetics; Computer science","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":[0.001978756,0.001914414,0.002173329,0.004305308,0.001603105,0.002943456,0.003498955,0.0006256716,0.01813383],"category_scores_gemma":[0.002727151,0.001083936,0.00159731,0.007908515,0.0003807229,0.001830952,0.003031536,0.00233551,0.01333269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001613685,"about_ca_system_score_gemma":0.002454371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01526246,"about_ca_topic_score_gemma":0.01312293,"domain_scores_codex":[0.9989096,0.0002147346,0.0001731791,0.0002120431,0.0003896704,0.0001008304],"domain_scores_gemma":[0.9991469,0.0001417907,0.0000521165,0.0003709669,0.0001618142,0.0001262473],"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":[0.001880539,0.0004128865,0.006933059,0.003873723,0.001005011,0.001240665,0.0009707243,0.0230992,0.04635219,0.04495571,0.7665983,0.102678],"study_design_scores_gemma":[0.0007833641,0.0001017052,0.010268,0.000505221,0.0002742507,0.0006482788,0.0004347731,0.04808068,0.02916474,0.05172347,0.8577009,0.0003146238],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.01766805,0.002118403,0.1327257,0.0009161526,0.0003289126,0.0008285085,0.6774315,0.1415563,0.02642641],"genre_scores_gemma":[0.04319602,0.002241669,0.1373932,0.0002617896,0.00004809918,0.001549717,0.7973525,0.01471673,0.003240282],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01813383,"threshold_uncertainty_score":0.06066364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03019394413057767,"score_gpt":0.2791532204173295,"score_spread":0.2489592762867519,"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."}}