{"id":"W4220991830","doi":"10.1038/s41467-022-28776-w","title":"Combinatorial optimization of mRNA structure, stability, and translation for RNA-based therapeutics","year":2022,"lang":"en","type":"article","venue":"Nature Communications","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":388,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of General Medical Sciences; National Science Foundation; Damon Runyon Cancer Research Foundation; Canadian Institutes of Health Research; Chemistry, Engineering and Medicine for Human Health, Stanford University; Stanford Bio-X; University of California, San Francisco; Baidu; Oregon State University; Pfizer; National Cancer Institute; National Institutes of Health","keywords":"Pseudouridine; Translation (biology); Messenger RNA; RNA; Ribosome; Computational biology; Stability (learning theory); Cell biology; Biology; Computer science; Transfer RNA; Biochemistry; Gene","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":[0.0006094312,0.0005060374,0.0006359278,0.0002595128,0.0002594722,0.0007951645,0.0003244498,0.0003506219,0.001298524],"category_scores_gemma":[0.0007579142,0.0003244377,0.0003725842,0.000272899,0.000436008,0.0004537148,0.0003480331,0.0007360676,0.0003912896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007855188,"about_ca_system_score_gemma":0.0005858836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002671354,"about_ca_topic_score_gemma":0.001198115,"domain_scores_codex":[0.999688,0.00007446527,0.00002432686,0.00007967942,0.00009821507,0.0000353785],"domain_scores_gemma":[0.9997395,0.0001072631,0.00007200913,0.00002713542,0.00002725597,0.00002688853],"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":[0.0002034144,0.000158754,0.0007158192,0.0002000286,0.00003135958,0.00008517844,0.00003032347,0.07209797,0.9067788,0.003652597,0.0002196013,0.0158261],"study_design_scores_gemma":[0.00004199575,0.0006271373,0.000646175,0.0000114755,0.00004892814,0.00006663951,0.00003147788,0.1929375,0.8008128,0.001660739,0.003083962,0.00003117331],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8143786,0.001504294,0.1764708,0.0002156085,0.00009409981,0.0001917396,0.000354723,0.0006232357,0.006166957],"genre_scores_gemma":[0.9123294,0.0010474,0.08430696,0.0001203477,0.00002110586,0.0001737337,0.0002491408,0.0001950416,0.001556881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001298524,"threshold_uncertainty_score":0.005699337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02928427736636944,"score_gpt":0.2900866515796698,"score_spread":0.2608023742133003,"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."}}