{"id":"W3012534023","doi":"10.1002/cbic.202000024","title":"In Vitro Selection of New DNA Aptamers for Human Vascular Endothelial Growth Factor 165","year":2020,"lang":"en","type":"article","venue":"ChemBioChem","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Aptamer; Systematic evolution of ligands by exponential enrichment; DNA; Biology; Computational biology; VEGF receptors; SELEX Aptamer Technique; In vitro; Molecular biology; Binding site; Chemistry; Biochemistry; Gene; Cancer research; 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":[0.0004671018,0.0004132038,0.000506408,0.0002630795,0.0001448837,0.0003345381,0.0002801052,0.0003346944,0.0006130826],"category_scores_gemma":[0.0006864223,0.0002681559,0.0002885242,0.0002042189,0.0001377833,0.0001588174,0.0003379767,0.0004584256,0.0003957323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002404697,"about_ca_system_score_gemma":0.0001367952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004233929,"about_ca_topic_score_gemma":0.0008560866,"domain_scores_codex":[0.999506,0.0001316869,0.00005690864,0.0001066438,0.0001490143,0.00004970557],"domain_scores_gemma":[0.9996355,0.0001331853,0.00006982386,0.00003491198,0.00007146367,0.00005508604],"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":[0.0000191243,0.00002097759,0.0001275885,0.00001411336,0.000002776688,0.00001113457,0.00001514833,0.0002114524,0.9983505,0.00002773075,0.00002241406,0.001177065],"study_design_scores_gemma":[0.000006993611,0.0002442576,0.0008110121,0.000003204062,0.000009789414,0.00006401594,0.000009963282,0.003275145,0.9943753,0.00001461342,0.001179186,0.000006530691],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9621609,0.0009107157,0.0344548,0.00008777734,0.0000594913,0.0003049778,0.0003992471,0.0002027129,0.001419231],"genre_scores_gemma":[0.8975101,0.0007228161,0.09380189,0.0001596256,0.00002023323,0.0002662584,0.001330629,0.0001196816,0.006068872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006130826,"threshold_uncertainty_score":0.002470315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0155201452747229,"score_gpt":0.2695027301074052,"score_spread":0.2539825848326823,"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."}}