{"id":"W4313454382","doi":"10.1021/acssynbio.2c00462","title":"Machine Learning Directed Aptamer Search from Conserved Primary Sequences and Secondary Structures","year":2023,"lang":"en","type":"article","venue":"ACS Synthetic Biology","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; University of Waterloo; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Aptamer; Computational biology; Sequence (biology); Systematic evolution of ligands by exponential enrichment; Sequence analysis; Protein secondary structure; Biology; Conserved sequence; Selection (genetic algorithm); Computer science; Artificial intelligence; Genetics; Base sequence; Gene; Biochemistry; RNA","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":[0.0007565896,0.0007222232,0.0009640951,0.0009298495,0.0004351485,0.0004412334,0.0007193036,0.0006401163,0.001382129],"category_scores_gemma":[0.001511999,0.0003189165,0.0005258342,0.0006499119,0.0003237175,0.0003928703,0.0004166793,0.0006637856,0.000364447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000516261,"about_ca_system_score_gemma":0.000950528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001359563,"about_ca_topic_score_gemma":0.001942058,"domain_scores_codex":[0.9995889,0.00009992065,0.00003544341,0.0001575276,0.00007249851,0.00004577079],"domain_scores_gemma":[0.9993256,0.0003564829,0.00007947889,0.00004203128,0.0001561809,0.00004024638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006469715,0.000521975,0.008706249,0.0003172664,0.000161242,0.0002941939,0.0001297118,0.326519,0.1304067,0.005269567,0.002868266,0.5241588],"study_design_scores_gemma":[0.00003026199,0.0001278197,0.0005738794,0.000004364795,0.00001960586,0.00006232388,0.00001074183,0.9813157,0.0158546,0.001400974,0.0005924149,0.000007301658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2086055,0.0005041515,0.7849202,0.0001366409,0.0000426791,0.0002467028,0.0002019882,0.002719862,0.002622281],"genre_scores_gemma":[0.5015894,0.0001774746,0.4948636,0.000192936,0.00002658677,0.0002753048,0.0007762061,0.0001477466,0.001950655],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001382129,"threshold_uncertainty_score":0.004623711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01412388952715324,"score_gpt":0.2717016576565557,"score_spread":0.2575777681294025,"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."}}