{"id":"W4221102522","doi":"10.1093/nar/gkac199","title":"ChIP-Atlas 2021 update: a data-mining suite for exploring epigenomic landscapes by fully integrating ChIP-seq, ATAC-seq and Bisulfite-seq data","year":2022,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":396,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Exploratory Research for Advanced Technology; National Bioscience Database Center; Japan Science and Technology Agency; Japan Society for the Promotion of Science; Ministry of Education, Culture, Sports, Science and Technology; Precursory Research for Embryonic Science and Technology; Kyoto University; Japan Agency for Medical Research and Development; Institute of Genetics; Support for Pioneering Research Initiated by the Next Generation","keywords":"Epigenomics; Biology; Computational biology; Genome browser; Genome; Genomics; DNA methylation; Chromatin; ChIP-sequencing; Database; Genetics; Computer science; Gene; Nucleosome; Gene expression","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005840309,0.003327116,0.003455226,0.005247912,0.001300816,0.004094135,0.005800497,0.001689119,0.02255311],"category_scores_gemma":[0.01063306,0.003609439,0.003105376,0.005254186,0.0005111254,0.002612921,0.00458443,0.003277009,0.02305964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001261028,"about_ca_system_score_gemma":0.004643417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006317411,"about_ca_topic_score_gemma":0.01740538,"domain_scores_codex":[0.99762,0.0004635628,0.0003682349,0.0005509761,0.0007744005,0.0002227495],"domain_scores_gemma":[0.9954332,0.001773319,0.0004586999,0.001137799,0.0008340582,0.0003628044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001097561,0.00008621476,0.008779979,0.005341442,0.002043637,0.0004862747,0.0004615065,0.004839454,0.02703902,0.006069743,0.8788546,0.06490063],"study_design_scores_gemma":[0.0006447585,0.0001295252,0.01296426,0.0004243627,0.001030034,0.001215735,0.0001305107,0.01532914,0.03724064,0.01346715,0.9170813,0.0003426011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.004384006,0.00273508,0.09401225,0.0005802547,0.0003691172,0.0004159451,0.7224942,0.1691442,0.005865109],"genre_scores_gemma":[0.008607822,0.001700886,0.1033587,0.0008560484,0.00008452444,0.001749438,0.8605439,0.02022631,0.002872346],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02255311,"threshold_uncertainty_score":0.07544768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1235807846163716,"score_gpt":0.3658882731827331,"score_spread":0.2423074885663616,"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."}}