{"id":"W1984734093","doi":"10.3389/fgene.2014.00431","title":"Pleiotropy constrains the evolution of protein but not regulatory sequences in a transcription regulatory network influencing complex social behaviors","year":2014,"lang":"en","type":"article","venue":"Frontiers in Genetics","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; York University","keywords":"Biology; Genetics; Gene regulatory network; Gene; Noncoding DNA; Conserved sequence; Pleiotropy; Regulatory sequence; Transcription factor; Negative selection; Evolutionary biology; Social connectedness; Molecular evolution; Computational biology; Phenotype; Phylogenetics; Genome; Gene expression; Peptide sequence","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":[0.0006340781,0.0002961626,0.0002632245,0.0005587011,0.0002791995,0.0004448953,0.0002332524,0.000370521,0.0008366147],"category_scores_gemma":[0.0008741698,0.000212114,0.0002424232,0.0003276149,0.0006593374,0.0003027551,0.000448434,0.0004165263,0.0001066795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002683265,"about_ca_system_score_gemma":0.0001807711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000588193,"about_ca_topic_score_gemma":0.001438624,"domain_scores_codex":[0.9996943,0.0001047684,0.0000159842,0.00009736637,0.00005386926,0.00003366076],"domain_scores_gemma":[0.9990492,0.0005054094,0.0002405357,0.00008239471,0.0000339053,0.00008841112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001691542,0.00003942417,0.04292784,0.00006451541,0.00006818255,0.0001811973,0.0002146549,0.003413219,0.9424399,0.001590604,0.00003900413,0.008852392],"study_design_scores_gemma":[0.00003977286,0.0002318578,0.8765404,0.00003369616,0.0001525692,0.0008533905,0.0003962256,0.04593307,0.06710689,0.00692126,0.001734596,0.00005625608],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954939,0.0001181405,0.003757163,0.00003108202,0.000002429429,0.000002938572,0.0000336834,0.00002271633,0.0005379464],"genre_scores_gemma":[0.9984005,0.00009330989,0.001358331,0.000025623,0.000003385565,0.000004215196,0.00003351061,0.000008894462,0.00007231646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008366147,"threshold_uncertainty_score":0.003353357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03031493370728446,"score_gpt":0.2064024380430289,"score_spread":0.1760875043357444,"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."}}