{"id":"W4410740430","doi":"10.1016/j.omtn.2025.102575","title":"Advantages, applications, and future directions of in vivo aptamer SELEX: A review","year":2025,"lang":"en","type":"review","venue":"Molecular Therapy — Nucleic Acids","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Centre","funders":"Research Grants Council, University Grants Committee; University Grants Committee","keywords":"Aptamer; Systematic evolution of ligands by exponential enrichment; Computational biology; Nanotechnology; Computer science; Biochemical engineering; Biology; Engineering; Materials science; Genetics; RNA","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009903819,0.0008908338,0.001128221,0.00225163,0.0002379173,0.001095564,0.000946122,0.00102948,0.003433845],"category_scores_gemma":[0.0009117037,0.0003539467,0.0005082333,0.001917858,0.0004201593,0.001552578,0.000740753,0.001756974,0.001885054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006168084,"about_ca_system_score_gemma":0.0009607684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007087978,"about_ca_topic_score_gemma":0.001718624,"domain_scores_codex":[0.9998086,0.00003256792,0.00002672399,0.00003472171,0.00007522583,0.00002222696],"domain_scores_gemma":[0.999516,0.0002742038,0.0000512022,0.00001092262,0.0001062138,0.00004147042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006215727,0.00006880202,0.0001339872,0.01509773,0.00008705182,0.000170506,0.00004731048,0.0005359032,0.002871934,0.00480932,0.03025142,0.9458638],"study_design_scores_gemma":[0.00001516401,0.00009050861,0.0003279235,0.002234578,0.00009743661,0.0007882087,0.00003367865,0.0001157002,0.0009481946,0.001790753,0.9935367,0.00002119014],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00009591999,0.9984515,0.000232766,0.0002453695,0.0001697958,0.000003796974,0.0000186184,0.000008231334,0.0007739605],"genre_scores_gemma":[0.0003518365,0.9986311,0.0002285261,0.0001898516,0.00009128294,0.000005749601,0.00002654186,0.00000179698,0.0004733791],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003433845,"threshold_uncertainty_score":0.01148736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00795773366503289,"score_gpt":0.310269590946841,"score_spread":0.3023118572818081,"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."}}