{"id":"W2145023212","doi":"10.1093/bioinformatics/btr657","title":"Prediction and analysis of nucleotide-binding residues using sequence and sequence-derived structural descriptors","year":2011,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":137,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Killam Trusts","keywords":"Sequence (biology); Computational biology; Sequence alignment; Peptide sequence; Sequence analysis; Nucleotide; Multiple sequence alignment; Protein sequencing; Binding site; Sequence logo; Sequence motif; Consensus sequence; Conserved sequence; Biology; Biochemistry; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002130249,0.0001631788,0.0002268757,0.0002038872,0.0001203814,0.00003420444,0.0001214308,0.0001313712,0.00001411185],"category_scores_gemma":[0.0001237278,0.0001471214,0.00005782142,0.0002402214,0.0002369248,0.00004445947,0.0001422742,0.00009225012,6.71984e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001784245,"about_ca_system_score_gemma":0.0000381757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000731999,"about_ca_topic_score_gemma":0.00001735336,"domain_scores_codex":[0.9990314,0.00002965666,0.0004758612,0.0001272427,0.0001455957,0.0001902934],"domain_scores_gemma":[0.9992514,0.00001194169,0.0003266417,0.0002430917,0.00008375175,0.0000831293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001038004,0.0000166267,0.5978204,0.000471091,0.001078687,0.000001993036,0.01144042,0.0007431892,0.3825969,0.0004510431,0.000060939,0.005214886],"study_design_scores_gemma":[0.0006273041,0.0004707671,0.1492639,0.00009826153,0.001031856,0.00008415028,0.002973565,0.756606,0.08804028,0.0000994066,0.000163915,0.0005406129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951564,0.00006537051,0.003899582,0.000004037565,0.00006800095,0.0001246756,0.0001065522,0.00002037624,0.0005549855],"genre_scores_gemma":[0.9081873,0.0001092488,0.09148451,0.00003546915,0.00001733885,0.000001435993,0.0001374803,0.00001026143,0.00001697941],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7558628,"threshold_uncertainty_score":0.5999437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05324823264434206,"score_gpt":0.2742169801333416,"score_spread":0.2209687474889996,"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."}}