Comparing Bayesian-Based Reconstruction Strategies in Topology-Based Pathway Enrichment Analysis.

ABSTRACT: The development of high-throughput omics technologies has enabled the quantification of vast amounts of genes and gene products in the whole genome. Pathway enrichment analysis (PEA) provides an intuitive solution for extracting biological insights from massive amounts of data. Topology-based pathway analysis (TPA) represents the latest generation of PEA methods, which exploit pathway topology in addition to lists of differentially expressed genes and their expression profiles. A subset of these TPA methods, such as BPA, BNrich, and PROPS, reconstruct pathway structures by training Bayesian networks (BNs) from canonical biological pathways, providing superior representations that explain causal relationships between genes. However, these methods have never been compared for their differenc

SUBMITTER: Wang Y 

PROVIDER: S-EPMC9313337 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature