Comparative epigenomics by machine learning approach for neuroblastoma.

ABSTRACT:

Background

Neuroblastoma (NB) is the second most common pediatric solid tumor. Because the number of genetic mutations found in tumors are small, even in some patients with unfavorable NB, epigenetic variation is expected to play an important role in NB progression. DNA methylation is a major epigenetic mechanism, and its relationship with NB prognosis has been a concern. One limitation with the analysis of variation in DNA methylation is the lack of a suitable analytical model. Therefore, in this study, we performed a random forest (RF) analysis of the DNA methylome data of NB from multiple databases.

Results

RF is a popular machine learning model owing to its simplicity, intuitiveness, and computational cost. RF analysis identified novel intermediate-risk patient groups wi

SUBMITTER: Sugino RP 

PROVIDER: S-EPMC9793522 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature