{"id":"W2967768859","doi":"10.1038/s41598-019-53726-w","title":"Engineering dual-glycan responsive expression systems for tunable production of heterologous proteins in Bacteroides thetaiotaomicron","year":2019,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Transgenic Plants and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada; Alberta Innovates; East Carolina University","keywords":"Bacteroides thetaiotaomicron; Glycan; Transgene; Arabinogalactan; Biology; Bacteroides; Computational biology; Heterologous; Synthetic biology; Cloning (programming); Heterologous expression; Cell biology; Gene; Bacteria; Biochemistry; Genetics; Recombinant DNA; Computer science; Glycoprotein; Polysaccharide","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":[0.0005201366,0.00007715064,0.0001155917,0.00006926659,0.00004179102,0.00002873866,0.0000570964,0.00006681212,0.000003005499],"category_scores_gemma":[0.00005937353,0.00006702421,0.00004440057,0.00008432427,0.00003242838,0.000007128845,0.00002395173,0.00003614425,0.000001534671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000116351,"about_ca_system_score_gemma":0.00005957544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001611875,"about_ca_topic_score_gemma":0.00001232263,"domain_scores_codex":[0.9990257,0.00001792629,0.0002706641,0.0004425949,0.00008768784,0.0001554195],"domain_scores_gemma":[0.9992794,0.000006792814,0.0001420319,0.0004723298,0.00007297053,0.00002650802],"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":[0.00004772783,0.00003398545,0.001089837,0.0000634652,0.000006103257,0.000001927071,0.00005283217,0.002530999,0.9953406,0.00000673318,0.0007752178,0.00005051848],"study_design_scores_gemma":[0.0001180802,0.00005386413,0.001372271,0.00005538746,0.000003873599,0.00006110244,0.00003710964,0.0001038321,0.9622615,0.00002640469,0.03582904,0.00007754174],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965779,0.0002029867,0.0003497302,0.00002721669,0.001721459,0.001071928,0.00001074559,0.000008445438,0.00002957968],"genre_scores_gemma":[0.9970629,0.000007898807,0.0003802507,0.000002112323,0.00005561901,0.0001522667,0.0001261932,0.00001024945,0.002202506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03505383,"threshold_uncertainty_score":0.2733168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006879305714591579,"score_gpt":0.2159140833035964,"score_spread":0.2090347775890048,"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."}}