{"id":"W2592243077","doi":"10.1088/1478-3975/aa64a4","title":"An evolution-based strategy for engineering allosteric regulation","year":2017,"lang":"en","type":"article","venue":"Physical Biology","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hillsborough Hospital","funders":"NIH Office of the Director; National Institutes of Health; Gordon and Betty Moore Foundation","keywords":"Allosteric regulation; Synthetic biology; Protein engineering; Computational biology; Rational design; Computer science; Biology; Enzyme; Biochemistry; Genetics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0000737383,0.00009480664,0.0001046328,0.00001358776,0.000132073,0.00002554449,0.0002101931,0.0001022423,0.000005248727],"category_scores_gemma":[0.00007565623,0.00008579969,0.00006819113,0.000009537307,0.0000437617,0.000004841535,0.00002253277,0.00002533777,0.000005730918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007010525,"about_ca_system_score_gemma":0.00002652013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000129982,"about_ca_topic_score_gemma":0.000003674917,"domain_scores_codex":[0.9994683,0.00002579771,0.00007442234,0.0002409837,0.00002667979,0.0001637899],"domain_scores_gemma":[0.9994196,0.00001669561,0.0000670699,0.0004095059,0.00003991566,0.00004726423],"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":[0.00005526643,0.00003928745,0.0002142432,0.000006861449,0.00001133247,8.375069e-8,0.000002262016,0.0003676668,0.987523,0.006310925,0.00002416366,0.005444972],"study_design_scores_gemma":[0.0003875611,0.0009782697,0.006349232,0.000005187564,0.00001297446,7.143684e-7,0.000002941823,0.01845355,0.9626987,0.007053484,0.003868877,0.0001885353],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7863414,0.00003599089,0.2130584,0.0001063189,0.00009406175,0.0001921111,0.00002534109,0.00001821206,0.0001282147],"genre_scores_gemma":[0.997317,0.000001149792,0.001829851,0.00003537179,0.0005458777,0.00007301214,0.0001348809,0.00001301563,0.00004984644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2112285,"threshold_uncertainty_score":0.349881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01979585103604132,"score_gpt":0.2945873012760785,"score_spread":0.2747914502400372,"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."}}