{"id":"W2979694653","doi":"10.1049/enb.2019.0009","title":"Engineered gene networks enable non‐genetic drug resistance and enhanced cellular robustness","year":2019,"lang":"en","type":"article","venue":"Engineering Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Gene; Gene regulatory network; Gene expression; Drug resistance; Robustness (evolution); Computational biology; Regulation of gene expression; Biological network; Genetics; Multiple drug resistance; Systems biology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001575399,0.000278898,0.000320608,0.00008205863,0.00004516595,0.000018245,0.000222825,0.0002535057,0.00002957164],"category_scores_gemma":[0.0000205668,0.0002898593,0.00009620322,0.0001878769,0.00004320799,0.000003581193,0.0001282012,0.0001343738,0.000009995315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001953266,"about_ca_system_score_gemma":0.00002595025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004307853,"about_ca_topic_score_gemma":0.000009279665,"domain_scores_codex":[0.9985909,0.00003866575,0.000252328,0.0005728436,0.00006363153,0.0004815869],"domain_scores_gemma":[0.999191,0.00002109694,0.00006675692,0.0005501436,0.00005317025,0.0001177631],"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":[0.00001363318,0.000006967109,0.0005092137,0.00002244274,0.00007757321,0.000001658867,0.000009423626,0.3994919,0.5995507,0.00001996571,0.0001832827,0.0001132635],"study_design_scores_gemma":[0.0009374407,0.0001068176,0.002554404,0.00003517954,0.00007717824,0.00001233778,0.00001540233,0.1550613,0.8230471,0.00001724943,0.01732254,0.0008130426],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8206525,0.006293471,0.1723925,0.00002610997,0.000347111,0.0001682154,0.000003285158,0.00003437675,0.00008232764],"genre_scores_gemma":[0.9901887,0.0003863465,0.006432724,0.00003208311,0.0003923345,0.00003027806,0.0001213149,0.0000537805,0.002362489],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2444306,"threshold_uncertainty_score":0.9999554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.001798804833766524,"score_gpt":0.1640314562159843,"score_spread":0.1622326513822178,"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."}}