Integration of Protein-Protein Interaction Networks and Gene Expression Profiles Helps Detect Pancreatic Adenocarcinoma Candidate Genes.

ABSTRACT: More and more cancer-associated genes (CAGs) are being identified with the development of biological mechanism research. Integrative analysis of protein-protein interaction (PPI) networks and co-expression patterns of these genes can help identify new disease-associated genes and clarify their importance in specific diseases. This study proposed a PPI network and co-expression integration analysis model (PRNet) to integrate PPI networks and gene co-expression patterns to identify potential risk causative genes for pancreatic adenocarcinoma (PAAD). We scored the importance of the candidate genes by constructing a high-confidence co-expression-based edge-weighted PPI network, extracting protein regulatory sub-networks by random walk algorithm, constructing disease-specific networks based on

SUBMITTER: Su L 

PROVIDER: S-EPMC9197464 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature