{"id":"W2063502259","doi":"10.1016/j.pep.2011.08.030","title":"A screening strategy for heterologous protein expression in Escherichia coli with the highest return of investment","year":2011,"lang":"en","type":"article","venue":"Protein Expression and Purification","topic":"Protein purification and stability","field":"Biochemistry, Genetics and Molecular Biology","cited_by":55,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Structural Genomics Consortium","funders":"Canadian Institutes of Health Research; Knut och Alice Wallenbergs Stiftelse; Karolinska Institutet; Stiftelsen för Strategisk Forskning; Ontario Innovation Trust; Wellcome Trust; Petroleum Technology Research Centre; Novartis Foundation; Merck; GlaxoSmithKline","keywords":"Escherichia coli; Heterologous; Inclusion bodies; Heterologous expression; Recombinant DNA; Biology; Biochemistry; Target protein; Molecular biology; Chemistry; Computational biology; Gene","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":[0.001047327,0.001017659,0.001320975,0.001011408,0.0005502714,0.001279425,0.0007857157,0.0009736198,0.001441359],"category_scores_gemma":[0.001086212,0.0004406729,0.0008825462,0.001346527,0.0002888969,0.0006963395,0.0007227451,0.001253434,0.001466049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006019424,"about_ca_system_score_gemma":0.0007516315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008533291,"about_ca_topic_score_gemma":0.001356265,"domain_scores_codex":[0.9987546,0.0003038012,0.0001728678,0.000142474,0.0004784439,0.0001478396],"domain_scores_gemma":[0.9994165,0.0001567663,0.00007925147,0.0001134324,0.0001655883,0.00006849127],"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":[0.00007858959,0.0001149573,0.000184962,0.00006687192,0.00001092019,0.00009412662,0.00001820926,0.0000887807,0.9943945,0.0003153282,0.0002050872,0.004427626],"study_design_scores_gemma":[0.0000203493,0.0003940518,0.000755663,0.000008509749,0.0000453741,0.000414095,0.00003624905,0.001101812,0.9941884,0.0001470707,0.002872782,0.00001563328],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7436903,0.00200068,0.2387384,0.002152912,0.0002810686,0.001694002,0.002923377,0.001356743,0.007162591],"genre_scores_gemma":[0.7727382,0.002409543,0.2025457,0.0005165132,0.00005628762,0.0007734267,0.005586915,0.0003621345,0.0150114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001441359,"threshold_uncertainty_score":0.005538881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03396895658886245,"score_gpt":0.2531781952737515,"score_spread":0.219209238684889,"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."}}