{"id":"W4406164867","doi":"10.1021/acsnano.4c12259","title":"AI-Based Prediction of Protein Corona Composition on DNA Nanostructures","year":2025,"lang":"en","type":"article","venue":"ACS Nano","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Civil, Mechanical and Manufacturing Innovation; National Institute of General Medical Sciences; Translational Impacts; National Institutes of Health; Division of Chemical, Bioengineering, Environmental, and Transport Systems; Wellcome Trust; McKnight Foundation; BRAIN Foundation; University of California, San Diego; Alfred P. Sloan Foundation; University of California Berkeley; Burroughs Wellcome Fund; Simons Foundation; National Science Foundation; Camille and Henry Dreyfus Foundation; Philomathia Foundation; Gordon and Betty Moore Foundation; Helen Wills Neuroscience Institute, University of California Berkeley","keywords":"Nanostructure; Nanotechnology; DNA; DNA origami; DNA nanotechnology; Materials science; Biophysics; Computational biology; Chemistry; Biology; Biochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005636092,0.00009811435,0.000108004,0.00007076582,0.00005505029,0.000007090033,0.00008024156,0.0001332947,0.000001068836],"category_scores_gemma":[0.00002491965,0.00008342794,0.00006481644,0.000120141,0.00007205992,0.000001840113,0.00002403787,0.00005008177,4.898552e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000146613,"about_ca_system_score_gemma":0.00004106951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005362101,"about_ca_topic_score_gemma":0.000003991675,"domain_scores_codex":[0.9994209,0.00003822419,0.0001542702,0.0002044453,0.00008883502,0.00009326301],"domain_scores_gemma":[0.9995642,0.000005457227,0.0000722643,0.000246448,0.0000953599,0.00001632812],"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":[0.0001427739,0.00005138877,0.0002506151,0.00001413863,0.00002938961,4.34882e-7,0.000001456724,0.00001731089,0.9946307,0.0002082454,0.00106774,0.003585813],"study_design_scores_gemma":[0.0002569653,0.0003178458,0.0009946157,0.00007185587,0.00002229333,7.359441e-7,0.00000322275,0.00003701813,0.9934044,0.0002319222,0.004593082,0.00006599453],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958365,0.00008506441,0.002839568,0.0003522566,0.0000564293,0.0001985982,0.00005905182,0.0000368464,0.00053569],"genre_scores_gemma":[0.9974442,0.00001177318,0.001318436,0.0006552741,0.0000360328,0.000009354364,0.0002597444,0.000006390038,0.0002588675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003525342,"threshold_uncertainty_score":0.3402093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004933151810829255,"score_gpt":0.2530892833068406,"score_spread":0.2481561314960113,"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."}}