{"id":"W4282940655","doi":"10.1038/s42003-022-03475-w","title":"A streamlined strain engineering workflow with genome-wide screening detects enhanced protein secretion in Komagataella phaffii","year":2022,"lang":"en","type":"article","venue":"Communications Biology","topic":"Fungal and yeast genetics research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"JST-Mirai Program; Core Research for Evolutional Science and Technology; Institute of Genetics; Ministry of Education, Culture, Sports, Science and Technology; Japan Society for the Promotion of Science; Japan Science and Technology Agency; New Energy and Industrial Technology Development Organization; Ministry of Economy, Trade and Industry; Japan Agency for Medical Research and Development","keywords":"Secretion; Gene knockout; Gene; Mutant; Computational biology; Biology; Secretory protein; Genome; Protein engineering; Metabolic engineering; Workflow; Strain (injury); Synthetic biology; Cell biology; Genetics; Computer science; Biochemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007468117,0.001119909,0.0007556537,0.0006239687,0.0003704463,0.0008426693,0.0007180674,0.0005843905,0.0005635881],"category_scores_gemma":[0.0005776987,0.0003049591,0.0006746787,0.0004783529,0.0003427099,0.0004615216,0.0008843148,0.001182952,0.0006574825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003523246,"about_ca_system_score_gemma":0.0004525177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001525662,"about_ca_topic_score_gemma":0.0026917,"domain_scores_codex":[0.999094,0.0001442403,0.0001192314,0.0002166578,0.000349257,0.00007662253],"domain_scores_gemma":[0.9994978,0.0001094002,0.0001190178,0.0001306267,0.00008630064,0.00005691132],"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":[0.00002222488,0.00002614174,0.0003663412,0.00002348418,0.000006529026,0.00003208842,0.000009931357,0.00007970847,0.9971318,0.000030126,0.00003447046,0.002237125],"study_design_scores_gemma":[0.000006959032,0.0001494351,0.002910394,0.000003609678,0.00001748685,0.00018929,0.00001709723,0.00132733,0.9942621,0.0000341315,0.001068916,0.00001310324],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7544361,0.0009283231,0.2372938,0.0003800016,0.00009601465,0.0004983955,0.002511009,0.002434582,0.00142171],"genre_scores_gemma":[0.6854742,0.001708286,0.3012168,0.0002345971,0.00002764394,0.0006074777,0.006539801,0.0004313927,0.003759853],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001525662,"threshold_uncertainty_score":0.003949583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01723368190097015,"score_gpt":0.2646902390732336,"score_spread":0.2474565571722634,"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."}}