PPIGCF: A Protein-Protein Interaction-Based Gene Correlation Filter for Optimal Gene Selection.

ABSTRACT: Biological data at the omics level are highly complex, requiring powerful computational approaches to identifying significant intrinsic characteristics to further search for informative markers involved in the studied phenotype. In this paper, we propose a novel dimension reduction technique, protein-protein interaction-based gene correlation filtration (PPIGCF), which builds on gene ontology (GO) and protein-protein interaction (PPI) structures to analyze microarray gene expression data. PPIGCF first extracts the gene symbols with their expression from the experimental dataset, and then, classifies them based on GO biological process (BP) and cellular component (CC) annotations. Every classification group inherits all the information on its CCs, corresponding to the BPs, to establish a PP

SUBMITTER: Pati SK 

PROVIDER: S-EPMC10218330 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature