ArticleBMC systems biology2012
Centrality-based pathway enrichment: a systematic approach for finding significant pathways dominated by key genes.
Article in BMC systems biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
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Who cites it
47 citing papers in PubMed.
- Spectral divergence prioritizes key classes, genes, and pathways shared between substance use disorders and cardiovascular disease.Frontiers in neuroscience · 2025Article
- Distribution of centrality measures on undirected random networks via the cavity method.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Ant colony optimization for the identification of dysregulated gene subnetworks from expression data.BMC bioinformatics · 2024Article
- RCPA: An Open-Source R Package for Data Processing, Differential Analysis, Consensus Pathway Analysis, and Visualization.Current protocols · 2024Article
- MicroRNAs in the Pathogenesis of Preeclampsia-A Case-Control In Silico Analysis.Current issues in molecular biology · 2024Article
- Gene set correlation enrichment analysis for interpreting and annotating gene expression profiles.Nucleic acids research · 2024Article
- Data Mining of Microarray Datasets in Translational Neuroscience.Brain sciences · 2023Review
- Pathway expression analysis.Scientific reports · 2022Article
- A comprehensive survey of the approaches for pathway analysis using multi-omics data integration.Briefings in bioinformatics · 2022Review
- On the influence of several factors on pathway enrichment analysis.Briefings in bioinformatics · 2022Review
- Clinical diagnosis of metabolic disorders using untargeted metabolomic profiling and disease-specific networks learned from profiling data.Scientific reports · 2022Article
- An Interaction-Based Method for Refining Results From Gene Set Enrichment Analysis.Frontiers in genetics · 2022Article
- GPCRs Are Optimal Regulators of Complex Biological Systems and Orchestrate the Interface between Health and Disease.International journal of molecular sciences · 2021Review
- PlantPathMarks (PPMdb): an interactive hub for pathways-based markers in plant genomes.Scientific reports · 2021Article
- CPA: a web-based platform for consensus pathway analysis and interactive visualization.Nucleic acids research · 2021Article
- netgsa: Fast computation and interactive visualization for topology-based pathway enrichment analysis.PLoS computational biology · 2021Article
- SIGNAL: A web-based iterative analysis platform integrating pathway and network approaches optimizes hit selection from genome-scale assays.Cell systems · 2021Article
- CTD: An information-theoretic algorithm to interpret sets of metabolomic and transcriptomic perturbations in the context of graphical models.PLoS computational biology · 2021Article
- Short Report: Using Targeted Urine Metabolomics to Distinguish Between Manganese Exposed and Unexposed Workers in a Small Occupational Cohort.Frontiers in public health · 2021Article
- PathExNET: A tool for extracting pathway expression networks from gene expression statistics.Computational and structural biotechnology journal · 2021Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBiological pathways are important for understanding biological mechanisms. Thus, finding important pathways that underlie biological problems helps researchers to focus on the most relevant sets of genes. Pathways resemble networks with complicated structures, but most of the existing pathway enrichment tools ignore topological information embedded within pathways, which limits their applicability.
resultsA systematic and extensible pathway enrichment method in which nodes are weighted by network centrality was proposed. We demonstrate how choice of pathway structure and centrality measurement, as well as the presence of key genes, affects pathway significance. We emphasize two improvements of our method over current methods. First, allowing for the diversity of genes' characters and the difficulty of covering gene importance from all aspects, we set centrality as an optional parameter in the model. Second, nodes rather than genes form the basic unit of pathways, such that one node can be composed of several genes and one gene may reside in different nodes. By comparing our methodology to the original enrichment method using both simulation data and real-world data, we demonstrate the efficacy of our method in finding new pathways from biological perspective.
conclusionsOur method can benefit the systematic analysis of biological pathways and help to extract more meaningful information from gene expression data. The algorithm has been implemented as an R package CePa, and also a web-based version of CePa is provided.
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