{"id":"W4406170049","doi":"10.1021/acs.accounts.4c00580","title":"Sequence-Defined DNA Polymers: New Tools for DNA Nanotechnology and Nucleic Acid Therapy","year":2025,"lang":"en","type":"article","venue":"Accounts of Chemical Research","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Killam Trusts; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Fonds de recherche du Québec – Nature et technologies; Canada Council for the Arts; Canada Research Chairs; Government of Canada","keywords":"DNA nanotechnology; Supramolecular chemistry; DNA origami; DNA; Nanotechnology; Stacking; Materials science; Supramolecular polymers; Sticky and blunt ends; Sequence (biology); Polymer; Self-assembly; Base pair; Nanostructure; Molecule; Chemistry","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":[0.0003987561,0.0005168621,0.0002841273,0.0007453099,0.0001671576,0.0006509989,0.0003935872,0.0004882402,0.002155282],"category_scores_gemma":[0.0004238371,0.0002666881,0.0002502302,0.0003249612,0.0007019021,0.001110418,0.0006270076,0.001434525,0.0008900228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004381577,"about_ca_system_score_gemma":0.0003396295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000141568,"about_ca_topic_score_gemma":0.0002284572,"domain_scores_codex":[0.9997621,0.00004970859,0.00001530313,0.00004565064,0.0001068771,0.00002037221],"domain_scores_gemma":[0.9998405,0.00004753212,0.00004705018,0.00001621233,0.00001896852,0.00002975534],"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":[0.0001382382,0.0001628769,0.0002998098,0.0009396378,0.00002792905,0.0002437713,0.0001730103,0.001840991,0.6866417,0.1065683,0.003841201,0.1991225],"study_design_scores_gemma":[0.00007144147,0.0005385585,0.0004395737,0.0001652064,0.00003255909,0.0008089957,0.00004669598,0.005976729,0.6471285,0.018966,0.3257656,0.00006023048],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1346449,0.3412968,0.4668546,0.007294696,0.002846301,0.0004847441,0.00111329,0.001899051,0.04356559],"genre_scores_gemma":[0.4829017,0.1715098,0.3107049,0.002940839,0.001251011,0.0007442721,0.0009079755,0.0003091306,0.02873039],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002155282,"threshold_uncertainty_score":0.007210135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05759631778559084,"score_gpt":0.3890039271937361,"score_spread":0.3314076094081452,"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."}}