{"id":"W4220841403","doi":"10.1016/j.csbj.2022.03.023","title":"Integrating whole genome sequencing, methylation, gene expression, topologically associated domain information in regulatory mutation prediction: A study of follicular lymphoma","year":2022,"lang":"en","type":"article","venue":"Computational and Structural Biotechnology Journal","topic":"Cancer-related gene regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network","funders":"Helse Sør-Øst RHF; Radiumhospitalets Forskningsstifltelse; Norges Forskningsråd","keywords":"DNA methylation; Biology; Genetics; Computational biology; Epigenomics; Regulatory sequence; Differentially methylated regions; Genome; Epigenetics; Gene; Follicular lymphoma; Genomics; Regulation of gene expression; Gene expression; Lymphoma","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004120748,0.0001327405,0.0001743972,0.0002899417,0.000392298,0.0000246044,0.0001385116,0.0001965743,0.00001806601],"category_scores_gemma":[0.00009566882,0.0001247041,0.00004766358,0.0003103316,0.00009290291,0.00003777855,0.0001400198,0.0002377874,2.152341e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002354801,"about_ca_system_score_gemma":0.0001449481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001323492,"about_ca_topic_score_gemma":0.00001203101,"domain_scores_codex":[0.998552,0.0002247431,0.0005846619,0.0002046236,0.0002887709,0.0001452506],"domain_scores_gemma":[0.9991618,0.00001841947,0.0004804708,0.0001076625,0.0001939422,0.00003766568],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001944352,0.0000851251,0.006708168,0.000006727553,0.0001300048,0.00001103647,0.001823987,0.5161968,0.4682576,0.0002797802,0.00006452061,0.006241811],"study_design_scores_gemma":[0.01334296,0.00667092,0.7601222,0.00006273376,0.0001030442,0.00344972,0.02333984,0.08580209,0.05038379,0.05466401,0.001166688,0.0008920507],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9922436,0.0003787081,0.006582316,0.0002960741,0.0001538839,0.0002694513,0.00004901849,0.0000198529,0.000007058226],"genre_scores_gemma":[0.9967436,0.00001109348,0.002592026,0.0000429117,0.00004913452,0.00002134863,0.0005253751,0.000006907743,0.000007598209],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.753414,"threshold_uncertainty_score":0.5085285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005764190793955437,"score_gpt":0.2202445785285978,"score_spread":0.2144803877346424,"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."}}