{"id":"W2108543631","doi":"10.1038/nbt919","title":"Integration of chemical-genetic and genetic interaction data links bioactive compounds to cellular target pathways","year":2003,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":695,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Cancer Institute; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Biology; Computational biology; Genetic screen; Gene; Chemical genetics; Genetics; Mechanism (biology); Mechanism of action; Yeast; Mutant; In vitro","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":[0.000641872,0.0007769587,0.0008391365,0.001969649,0.0003853359,0.001312728,0.0006868182,0.0007437897,0.00285806],"category_scores_gemma":[0.001196539,0.0004607275,0.000686753,0.001556294,0.0006878174,0.001505638,0.0007069885,0.001248814,0.001268878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007441439,"about_ca_system_score_gemma":0.0004527554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003908875,"about_ca_topic_score_gemma":0.000622219,"domain_scores_codex":[0.9994604,0.00008491892,0.00003685831,0.00010475,0.0002819103,0.00003127981],"domain_scores_gemma":[0.9985484,0.0006601445,0.000356716,0.0001669392,0.000188136,0.00007959329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005251166,0.0001326798,0.001470528,0.0003038762,0.00007055984,0.0002471302,0.00001269343,0.00173747,0.9702305,0.005962369,0.0002877696,0.01901937],"study_design_scores_gemma":[0.00002996041,0.0001948231,0.003201063,0.00001038553,0.0001075126,0.000367079,0.00001847142,0.004738952,0.9794606,0.00761834,0.004224159,0.00002847691],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5308056,0.0139559,0.3934216,0.003469246,0.0006455933,0.0003300952,0.009712854,0.003667461,0.04399169],"genre_scores_gemma":[0.9234204,0.007535138,0.05856751,0.0007548767,0.0002380289,0.0001558635,0.005283993,0.0001808404,0.003863242],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00285806,"threshold_uncertainty_score":0.009561181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01327483873614197,"score_gpt":0.2453674095014666,"score_spread":0.2320925707653246,"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."}}