{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003142207,0.0004090916,0.0002383001,0.0001644009,0.0001093095,0.0003480205,0.0002407523,0.0002731229,0.0003378813],"category_scores_gemma":[0.000174897,0.0001665067,0.0002208644,0.0002009704,0.0002230615,0.0002512697,0.0003992209,0.0006946192,0.0002698267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003936371,"about_ca_system_score_gemma":0.0002457623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006460992,"about_ca_topic_score_gemma":0.0006220808,"domain_scores_codex":[0.9998362,0.00002420785,0.00001576629,0.00003715059,0.00005159,0.00003501687],"domain_scores_gemma":[0.9999044,0.00001483056,0.00003753554,0.000009200781,0.00001234461,0.00002162271],"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":[0.00001260642,0.000005390688,0.00003468672,0.00001114205,8.27248e-7,0.000007825265,0.000006371416,0.00003404642,0.9995624,0.00003848749,0.000004978863,0.0002812293],"study_design_scores_gemma":[0.000007456014,0.0000555801,0.0004483297,0.000002572536,0.000005559312,0.00004156149,0.0000149678,0.0007734798,0.9976857,0.00002155191,0.0009389847,0.000004221959],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9747867,0.0005249928,0.02337543,0.0001563791,0.00003271147,0.00005522365,0.0002527905,0.000130277,0.0006853252],"genre_scores_gemma":[0.9700993,0.0007368093,0.0263414,0.00005059411,0.000006520777,0.00007190605,0.0004831092,0.00008306122,0.002127318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006460992,"threshold_uncertainty_score":0.002856076,"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."}}