{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000177092,0.0001358117,0.0001644053,0.0001024321,0.0001372691,0.000008782675,0.0001121083,0.0001052214,0.00001115027],"category_scores_gemma":[0.0001413556,0.0001300453,0.00004022876,0.0001163257,0.00005081419,0.00000207487,0.00008981222,0.000102684,0.000009249229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003592846,"about_ca_system_score_gemma":0.00002774746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000527822,"about_ca_topic_score_gemma":0.000007317899,"domain_scores_codex":[0.9990078,0.0001787845,0.0001686027,0.0003799137,0.0000547116,0.0002101476],"domain_scores_gemma":[0.9996157,0.00001350521,0.00004936522,0.0002318787,0.00002216556,0.00006739818],"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":[0.0001293873,0.00002197687,0.0001294813,0.00002048136,0.00003087852,9.358964e-7,0.0002848014,0.00006626244,0.9961527,0.00005621045,0.000129655,0.002977232],"study_design_scores_gemma":[0.0005510387,0.0007067767,0.001537574,0.00001605019,0.00002840532,0.000162478,0.001116571,0.00005613475,0.9339532,0.00001178179,0.06158487,0.0002750982],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978586,0.0003254515,0.0003974812,0.0003259489,0.0005997798,0.0002995731,0.0001176635,0.00003589749,0.00003960522],"genre_scores_gemma":[0.9990278,0.00002051464,0.0004173691,0.0001226274,0.0001241095,0.000074376,0.00005819115,0.00001789104,0.0001371569],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06219948,"threshold_uncertainty_score":0.5303093,"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."}}