{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000694311,0.0008379219,0.0007504874,0.001699018,0.0002991186,0.0005180706,0.000573416,0.0005378157,0.002573912],"category_scores_gemma":[0.001819941,0.0002141161,0.0005485232,0.00150911,0.0002283647,0.0005035414,0.0003952399,0.0006487395,0.001703318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005088843,"about_ca_system_score_gemma":0.0008253098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00256924,"about_ca_topic_score_gemma":0.004739906,"domain_scores_codex":[0.9997222,0.00005399076,0.00001810464,0.00008743862,0.00008820404,0.00003009862],"domain_scores_gemma":[0.9992232,0.0003440786,0.000141522,0.00005643151,0.0001519667,0.00008272071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002004312,0.001149415,0.1426285,0.001299958,0.0004125331,0.001166211,0.0001495887,0.4579119,0.1423053,0.003012318,0.01946664,0.2284933],"study_design_scores_gemma":[0.00006053433,0.0002565118,0.01783865,0.00004445552,0.00011381,0.0003741801,0.00004734978,0.9467272,0.02793917,0.002377656,0.004186092,0.00003438977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7725428,0.001713235,0.1959145,0.0003600215,0.00006279009,0.000212617,0.02063572,0.005223982,0.003334176],"genre_scores_gemma":[0.8655009,0.0007592326,0.0852695,0.0001036005,0.00004528372,0.0001504325,0.04637469,0.0003058731,0.001490436],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002573912,"threshold_uncertainty_score":0.008610606,"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."}}