{"id":"W4221066348","doi":"10.1021/acssynbio.2c00063","title":"A Versatile Transcription Factor Biosensor System Responsive to Multiple Aromatic and Indole Inducers","year":2022,"lang":"en","type":"article","venue":"ACS Synthetic Biology","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; PROTEO","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Concordia University","keywords":"TetR; Synthetic biology; Biosensor; Computational biology; Metabolic engineering; Biology; Indole test; Transcription factor; Protein engineering; Directed evolution; Repressor; Biochemistry; Gene; Enzyme","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":[0.0003989023,0.0006309785,0.0005066893,0.0003675859,0.000245686,0.000415803,0.0008487882,0.0007410072,0.001617574],"category_scores_gemma":[0.0003336714,0.0002700295,0.0003550077,0.0002436746,0.0003761096,0.0004572945,0.0005111602,0.001193518,0.0009340583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007377333,"about_ca_system_score_gemma":0.0003644188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006683672,"about_ca_topic_score_gemma":0.0009888394,"domain_scores_codex":[0.9993134,0.00007557598,0.00003610902,0.0002266919,0.0002635711,0.00008467677],"domain_scores_gemma":[0.9998071,0.00003849294,0.00004514905,0.00002214418,0.00002894029,0.00005822014],"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":[0.00002064126,0.000009593873,0.00001640468,0.00001346571,0.000001397815,0.00001002357,0.000004034195,0.00002599703,0.9988908,0.00009077386,0.00006748604,0.0008494029],"study_design_scores_gemma":[0.000009088434,0.00005393993,0.0002047984,0.000002183597,0.000004130214,0.0001324772,0.0000042749,0.001015064,0.99657,0.00003656671,0.001959724,0.000007643016],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.660816,0.003211083,0.3133517,0.001859262,0.0005389957,0.000467481,0.004342294,0.007407124,0.008006114],"genre_scores_gemma":[0.8597258,0.00145528,0.1219177,0.000392358,0.0001037135,0.0004509958,0.00478396,0.0002379302,0.01093226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001617574,"threshold_uncertainty_score":0.005411327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009632791498810776,"score_gpt":0.2138314682910142,"score_spread":0.2041986767922034,"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."}}