{"id":"W4312018781","doi":"10.1093/bioinformatics/btac813","title":"Integrative chromatin domain annotation through graph embedding of Hi-C data","year":2022,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Compute Canada","keywords":"Annotation; Chromatin; Computational biology; Genome; Embedding; Domain (mathematical analysis); Pairwise comparison; Epigenomics; Genomics; Computer science; Graph; Biology; Genetics; Theoretical computer science; Artificial intelligence; Gene; DNA methylation; Gene expression; Mathematics","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":[0.0005153239,0.00105707,0.0005662423,0.002175482,0.0004338842,0.0009248357,0.001591716,0.001206577,0.002801987],"category_scores_gemma":[0.002470549,0.0004334061,0.0009953419,0.001715411,0.0004641796,0.001209128,0.001173322,0.001260719,0.0016094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007377993,"about_ca_system_score_gemma":0.0006269535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007053038,"about_ca_topic_score_gemma":0.01298239,"domain_scores_codex":[0.9995764,0.00007694944,0.00001399245,0.0002207825,0.00007030267,0.00004157573],"domain_scores_gemma":[0.9990456,0.0004054786,0.00008103218,0.0002338875,0.0001683393,0.00006579066],"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":[0.001009564,0.0005157546,0.02542521,0.00162633,0.0004842075,0.0007830253,0.0006056763,0.4575543,0.1057225,0.02474913,0.05935949,0.3221648],"study_design_scores_gemma":[0.00002206254,0.00004219902,0.003404591,0.00003478302,0.00004392287,0.000124345,0.00007339783,0.9578993,0.01110292,0.01880984,0.008408268,0.00003424614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09287519,0.0006628074,0.8545838,0.0005521004,0.00008996673,0.0001976413,0.02783413,0.02039369,0.002810758],"genre_scores_gemma":[0.4154758,0.0004111334,0.490829,0.0003488548,0.0000627609,0.0002732105,0.08772738,0.001746643,0.003125122],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007053038,"threshold_uncertainty_score":0.01402396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01531051330598558,"score_gpt":0.267753883033361,"score_spread":0.2524433697273754,"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."}}