DAGBagM: learning directed acyclic graphs of mixed variables with an application to identify protein biomarkers for treatment response in ovarian cancer - Chowdhury, Shrabanti; Wang, Ru; Yu, Qing; Huntoon, Catherine J.; Karnitz, Larry M.; Kaufmann, Scott H.; Gygi, Steven P.; Birrer, Michael J.; Paulovich, Amanda G.; Peng, Jie; Wang, Pei (BMC bioinformatics, 2022)
Keywords: Algorithms; Bioinformatics; Biomarkers; Biomedical and Life Sciences; Bootstrap aggregation; Cancer; Cancer therapies; Care and treatment; Causality; Child; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Computer Simulation; Confounding Factors, Epidemiologic; Continuity (mathematics); Development and progression; Diagnosis; Experiments; Female; Graph theory; Hill climbing; Humans; Identification and classification; Learning; Life Sciences; Methods; Microarrays; Nodes; Oncology, Experimental; Ovarian cancer; Ovarian Neoplasms - drug therapy; Ovarian Neoplasms - genetics; Performance evaluation; Proteins; Proteomics; Random variables; Sensitive and resistant/refractory; Simulation; Tumor markers; United States; Hill climbing; Bootstrap aggregation; Sensitive and resistant/refractory; Proteomics