DAGBagM: learning directed acyclic graphs of mixed variables with an application to identify protein biomarkers for treatment response in ovarian cancer

BACKGROUND: Applying directed acyclic graph (DAG) models to proteogenomic data has been shown effective for detecting causal biomarkers of complex diseases. However, there remain unsolved challenges in DAG learning to jointly model binary clinical outcome variables and continuous biomarker measureme...

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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9354326/
https://www.ncbi.nlm.nih.gov/pubmed/35931981
http://dx.doi.org/10.1186/s12859-022-04864-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9354326/
https://www.ncbi.nlm.nih.gov/pubmed/35931981
http://dx.doi.org/10.1186/s12859-022-04864-y

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