Determination of biomarkers from microarray data using graph neural network and spectral clustering.

ABSTRACT: In bioinformatics, the rapid development of gene sequencing technology has produced an increasing amount of microarray data. This type of data shares the typical characteristics of small sample size and high feature dimensions. Searching for biomarkers from microarray data, which expression features of various diseases, is essential for the disease classification. feature selection has therefore became fundemental for the analysis of microarray data, which designs to remove irrelevant and redundant features. There are a large number of redundant features and irrelevant features in microarray data, which severely degrade the classification effectiveness. We propose an innovative feature selection method with the goal of obtaining feature dependencies from a priori knowledge and removing red

SUBMITTER: Yu K 

PROVIDER: S-EPMC8668890 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature