2026-10-10T06:29:13Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33814284 2026-09-15T17:57:16Z category_12 category_13 category_14 category_734 category_132 category_133 portal_5 item_type_3 month_year_09_2026

<p>Module-level AUCs derived from mean based RNA-only global networks. These results show which modules are most informative for subtype prediction as an ablation study.</p> Alejandro Leyva (12268024) M. Khalid Khan Niazi (17818678) Cell Biology Genetics Molecular Biology Biological Sciences not elsewhere classified Infectious Diseases Plant Biology obtain network estimates improve subtype classification characterize biological pathways cancer genome atlas networks remains unclear multimodal lioness networks individualized lioness networks timing proxies tcga ). specific integration single samples rna modules rna expression replication timing morphological embeddings mean degree linear interpolation gene modules findings show every fold derived replication basal like <p>Module-level AUCs derived from mean based RNA-only global networks. These results show which modules are most informative for subtype prediction as an ablation study.</p> 2026-09-15T17:57:03Z Dataset Dataset 10.1371/journal.pone.0358246.t004 https://figshare.com/articles/dataset/_p_Module-level_AUCs_derived_from_mean_based_RNA-only_global_networks_These_results_show_which_modules_are_most_informative_for_subtype_prediction_as_an_ablation_study_p_/33814284 CC BY 4.0