{"id":"W2582176104","doi":"10.1093/nar/gkx059","title":"DRNApred, fast sequence-based method that accurately predicts and discriminates DNA- and RNA-binding residues","year":2017,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":234,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Biology; RNA; DNA; RNA-binding protein; Computational biology; Binding site; Nucleic acid; HMG-box; DNA binding site; DNA-binding protein; Genetics; Transcription factor; Gene expression; Gene; Promoter","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00177601,0.000201185,0.0002111495,0.0001089748,0.001081046,0.0005217656,0.0005953081,0.0002677352,0.00004796508],"category_scores_gemma":[0.0007376532,0.0001695283,0.00004971913,0.000043888,0.0005379703,0.00003208218,0.0005892228,0.0002445826,0.000012928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001953368,"about_ca_system_score_gemma":0.0001005428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001079604,"about_ca_topic_score_gemma":0.00003873742,"domain_scores_codex":[0.9978563,0.0003867974,0.0001605312,0.0006204458,0.0004365308,0.0005393501],"domain_scores_gemma":[0.9986446,0.0001204967,0.00009842714,0.0007793208,0.0001341733,0.0002229374],"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":[0.0001810366,0.0000184575,0.003713687,0.00006808652,0.00003166588,0.00002046777,0.000159592,6.479897e-7,0.9448023,0.0002140948,0.0003350622,0.05045491],"study_design_scores_gemma":[0.0005318651,0.0003767919,0.00664824,0.00009669885,0.00001382693,0.00001835024,0.0003751331,0.0001882294,0.9864363,0.001105597,0.004001067,0.0002078967],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922438,0.0006211472,0.001177019,0.00110394,0.00007706435,0.0003809471,0.0000508073,0.00001915979,0.00432617],"genre_scores_gemma":[0.9912538,0.0006669168,0.006275425,0.00004494303,0.0001639821,0.00006104051,0.00002423175,0.00004006433,0.001469622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05024701,"threshold_uncertainty_score":0.8314644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.144269121357327,"score_gpt":0.3992052653880974,"score_spread":0.2549361440307705,"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."}}