{"id":"W4400656884","doi":"10.1186/s12920-024-01941-4","title":"Co-expression in tissue-specific gene networks links genes in cancer-susceptibility loci to known somatic driver genes","year":2024,"lang":"en","type":"article","venue":"BMC Medical Genomics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Research Council; Universitair Medisch Centrum Groningen; Oncode Institute; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Canadian Institutes of Health Research; Gray Foundation; Genome Canada; ZonMw; National Institutes of Health; Ovarian Cancer Research Fund; Cancer Research UK; Government of Canada; European Commission; Breast Cancer Research Foundation","keywords":"Genome-wide association study; Biology; Gene; Genetics; Somatic cell; Germline; Germline mutation; Cancer; Human genetics; Genome; Computational biology; Mutation; Single-nucleotide polymorphism; Genotype","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008184465,0.0003058522,0.0003716027,0.0001211142,0.00006233705,0.0000747899,0.0004855491,0.0008656093,0.0003075609],"category_scores_gemma":[0.00004773657,0.0002786013,0.0001083875,0.0002540752,0.0001217705,0.000008384223,0.0002678078,0.0005134809,0.00008726356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001919838,"about_ca_system_score_gemma":0.0004922949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006295207,"about_ca_topic_score_gemma":0.002372136,"domain_scores_codex":[0.9975945,0.0001175761,0.0007766919,0.0006359799,0.0002854701,0.0005897876],"domain_scores_gemma":[0.9989075,0.00007976589,0.00007370556,0.0005345513,0.00003676283,0.0003676901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002809105,0.0002850062,0.01431441,0.0006060716,0.00006617214,0.00009252851,0.001015139,0.06538329,0.4524209,0.0001023323,0.01676324,0.44867],"study_design_scores_gemma":[0.002183393,0.0004465679,0.007500263,0.0007988772,0.00003775005,0.00005492995,0.0003395883,0.2043549,0.1266803,0.0005187881,0.6555371,0.001547563],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8788059,0.03523253,0.08381364,0.0002218761,0.0009020251,0.0006308447,0.00003804335,0.00003216031,0.0003230338],"genre_scores_gemma":[0.9623536,0.02114004,0.01177121,0.0008561687,0.002569019,0.0001641624,0.000438804,0.00009099823,0.0006159559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6387738,"threshold_uncertainty_score":0.9999666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01635386893625475,"score_gpt":0.2845004242840825,"score_spread":0.2681465553478277,"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."}}