{"id":"W2808381662","doi":"10.7717/peerj.5062","title":"Transcriptional regulation of metabolism in disease: From transcription factors to epigenetics","year":2018,"lang":"en","type":"article","venue":"PeerJ","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Epigenetics; Biology; DNA methylation; Transcription factor; Transcriptional regulation; microRNA; Cell metabolism; Transcription (linguistics); Gene; Regulation of gene expression; Epigenomics; Histone; Computational biology; Genetics; Enhancer; Context (archaeology); Phenotype; Cell; Gene expression","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":[0.000732225,0.0004401762,0.0007355402,0.0006593076,0.0005402531,0.001462849,0.0004820599,0.001093391,0.002808557],"category_scores_gemma":[0.000815013,0.0001581464,0.000267401,0.0006096846,0.002677771,0.00208993,0.0009757561,0.001864202,0.001188289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007970356,"about_ca_system_score_gemma":0.0009843165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005177403,"about_ca_topic_score_gemma":0.0007870552,"domain_scores_codex":[0.9996529,0.00008668617,0.0000315151,0.00007225617,0.0001225554,0.00003421317],"domain_scores_gemma":[0.9995641,0.0001700306,0.00005467555,0.00002351752,0.0001252717,0.0000624611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002392202,0.00007465252,0.002856623,0.009687833,0.0001626101,0.003831822,0.003450231,0.0009038406,0.09417757,0.1160102,0.07769483,0.6909105],"study_design_scores_gemma":[0.0000117346,0.00009544134,0.003704028,0.000945554,0.000035137,0.003256164,0.0008359128,0.000207525,0.0111757,0.03768877,0.9420007,0.00004325785],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004584791,0.9522713,0.00602923,0.02096925,0.006711201,0.00001758845,0.00005909443,0.00009004132,0.009267571],"genre_scores_gemma":[0.03437925,0.9440835,0.003123519,0.002785634,0.006830459,0.00001622338,0.0000662483,0.00004320791,0.008671967],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002808557,"threshold_uncertainty_score":0.009395599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01729591903196543,"score_gpt":0.2623777756015665,"score_spread":0.2450818565696011,"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."}}