Dynamic Meta-data Network Sparse PCA for Cancer Subtype Biomarker Screening.

ABSTRACT: Previous research shows that each type of cancer can be divided into multiple subtypes, which is one of the key reasons that make cancer difficult to cure. Under these circumstances, finding a new target gene of cancer subtypes has great significance on developing new anti-cancer drugs and personalized treatment. Due to the fact that gene expression data sets of cancer are usually high-dimensional and with high noise and have multiple potential subtypes' information, many sparse principal component analysis (sparse PCA) methods have been used to identify cancer subtype biomarkers and subtype clusters. However, the existing sparse PCA methods have not used the known cancer subtype information as prior knowledge, and their results are greatly affected by the quality of the samples. Therefore

SUBMITTER: Miao R 

PROVIDER: S-EPMC9197542 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature