ArticleJournal of the Royal Society, Interface2015
A novel dysregulated pathway-identification analysis based on global influence of within-pathway effects and crosstalk between pathways.
Article in Journal of the Royal Society, Interface, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- ssMutPA: single-sample mutation-based pathway analysis approach for cancer precision medicine.GigaScience · 2024Article
- A pathway-based mutation signature to predict the clinical outcomes and response to CTLA-4 inhibitors in melanoma.Computational and structural biotechnology journal · 2023Article
- Tumor Microenvironment Characterization in Breast Cancer Identifies Prognostic Pathway Signatures.Genes · 2022Article
- Exploring autophagy-related prognostic genes of Alzheimer's disease based on pathway crosstalk analysis.Bosnian journal of basic medical sciences · 2022Article
- Identification of core pathways based on attractor and crosstalk in ischemic stroke.Experimental and therapeutic medicine · 2018Article
- LncRNAs2Pathways: Identifying the pathways influenced by a set of lncRNAs of interest based on a global network propagation method.Scientific reports · 2017Article
- Altered Pathway Analyzer: A gene expression dataset analysis tool for identification and prioritization of differentially regulated and network rewired pathways.Scientific reports · 2017Article
- Bayesian model of signal rewiring reveals mechanisms of gene dysregulation in acquired drug resistance in breast cancer.PloS one · 2017Article
- A Novel Method for Pathway Identification Based on Attractor and Crosstalk in Polyarticular Juvenile Idiopathic Arthritis.Medical science monitor : international medical journal of experimental and clinical research · 2016Article
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Authors and funding
14 authors.
Funding
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Abstract
Identifying dysregulated pathways from high-throughput experimental data in order to infer underlying biological insights is an important task. Current pathway-identification methods focus on single pathways in isolation; however, consideration of crosstalk between pathways could improve our understanding of alterations in biological states. We propose a novel method of pathway analysis based on global influence (PAGI) to identify dysregulated pathways, by considering both within-pathway effects and crosstalk between pathways. We constructed a global gene–gene network based on the relationships among genes extracted from a pathway database. We then evaluated the extent of differential expression for each gene, and mapped them to the global network. The random walk with restart algorithm was used to calculate the extent of genes affected by global influence. Finally, we used cumulative distribution functions to determine the significance values of the dysregulated pathways. We applied the PAGI method to five cancer microarray datasets, and compared our results with gene set enrichment analysis and five other methods. Based on these analyses, we demonstrated that PAGI can effectively identify dysregulated pathways associated with cancer, with strong reproducibility and robustness. We implemented PAGI using the freely available R-based and Web-based tools (http://bioinfo.hrbmu.edu.cn/PAGI).
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