{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004912724,0.0001622909,0.0001506603,0.00004323996,0.0001188069,0.0000189268,0.000197312,0.0001637438,0.00001268541],"category_scores_gemma":[0.00006781197,0.0001057094,0.00003807255,0.00009494353,0.0001580822,0.0000164207,0.0000510648,0.0001187329,4.004828e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009396225,"about_ca_system_score_gemma":0.00004764368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003050306,"about_ca_topic_score_gemma":0.00002052854,"domain_scores_codex":[0.9987532,0.0002151609,0.0003029805,0.0004057526,0.0001383362,0.000184513],"domain_scores_gemma":[0.999084,0.00001244325,0.0002679167,0.0004642411,0.0001022121,0.00006918242],"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":[0.0008994928,0.0001471006,0.000552208,0.00007259326,0.000006707594,2.293607e-7,0.0003568694,0.000006218647,0.9952303,0.0003099943,0.00004509156,0.002373228],"study_design_scores_gemma":[0.0008123918,0.0005012875,0.008759643,0.0001064728,0.000005516187,9.973153e-7,0.0002288851,0.0001265168,0.9848433,0.000497054,0.003975262,0.0001427245],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9714509,0.0009326916,0.0237468,0.000335291,0.00001212721,0.00314811,0.00001725305,0.00001702048,0.0003397685],"genre_scores_gemma":[0.9800487,0.00002135599,0.01742415,0.00007842026,0.00002680799,0.002142263,0.00006017514,0.00001713381,0.0001809713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01038702,"threshold_uncertainty_score":0.4310702,"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."}}