{"id":"W2085075228","doi":"10.1021/bi050293e","title":"Mutual Information in Protein Multiple Sequence Alignments Reveals Two Classes of Coevolving Positions","year":2005,"lang":"en","type":"article","venue":"Biochemistry","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":256,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Coevolution; Multiple sequence alignment; Set (abstract data type); Sequence (biology); Sequence alignment; Function (biology); Biology; Computational biology; Protein structure; Protein family; Mutual information; Computer science; Genetics; Evolutionary biology; Peptide sequence; Artificial intelligence; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003335504,0.0005281135,0.001011212,0.006849715,0.0008354866,0.001840428,0.0008038377,0.001062261,0.0007954543],"category_scores_gemma":[0.01566589,0.0004553663,0.0007716917,0.00386041,0.002262094,0.002614383,0.00160449,0.0009744021,0.0002492278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001196568,"about_ca_system_score_gemma":0.0005961382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008734884,"about_ca_topic_score_gemma":0.001273532,"domain_scores_codex":[0.9976404,0.0006650715,0.0002165316,0.0004778618,0.0007615744,0.0002384796],"domain_scores_gemma":[0.9888936,0.00769804,0.001615764,0.0008081176,0.0006216009,0.0003629027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00230414,0.0003979892,0.2653072,0.0009065128,0.001530288,0.003362141,0.00171377,0.2091379,0.06094249,0.1240133,0.003269232,0.3271151],"study_design_scores_gemma":[0.0000671897,0.0003503758,0.1139549,0.00009737754,0.0003425646,0.002034927,0.0003971384,0.6785011,0.0164969,0.1845792,0.003002996,0.0001754025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7487004,0.001622056,0.2443815,0.000471868,0.00003190454,0.00006690754,0.0005092128,0.0004348037,0.003781379],"genre_scores_gemma":[0.9823604,0.0002436915,0.01651925,0.00003667127,0.00003671985,0.0000331009,0.0004489167,0.00003380143,0.0002874953],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006849715,"threshold_uncertainty_score":0.01764005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007279509674066808,"score_gpt":0.2557520582365386,"score_spread":0.2484725485624718,"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."}}