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PINTnet: construction of condition-specific pathway interaction network by computing shortest paths on weighted PPI
Ji Hwan Moon1, Sangsoo Lim1, Kyuri Jo2
1Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
BMC Systems Biology
|April 1, 2017
Summary
We developed PINTnet, a novel method for identifying condition-specific perturbed pathways and their interactions. This approach considers pathway topology and gene expression data, outperforming existing methods in analyzing RNA-sequencing data.
Area of Science:
- Systems Biology
- Bioinformatics
- Genomics
Background:
- Pathway analysis is crucial for understanding biological phenomena.
- Current methods for pathway interaction prediction often overlook topological features and gene expression quantities.
- Existing approaches rely on gene overlap, protein-protein interactions (PPI), or functional similarities, neglecting pathway structure.
Purpose of the Study:
- To develop a novel method for constructing pathway interaction networks that incorporates topological features and gene expression data.
- To overcome limitations of existing pathway analysis tools by considering pathway structure and quantitative gene expression information.
- To identify condition-specific perturbed pathways and their interactions more effectively.
Main Methods:
- Developed a new pathway interaction network construction method named PINTnet.
- Utilized protein-protein interaction (PPI) data, closeness centrality, and shortest paths in network construction.
- Applied the method to analyze three high-throughput RNA-sequencing datasets: pregnant mice, bone-metastatic breast cancer, and autoimmune thyroiditis.
Main Results:
- PINTnet successfully identified condition-specific perturbed pathways and their interactions across three diverse datasets.
- The method validated pathways reported in original studies and uncovered new interactions supported by literature.
- PINTnet demonstrated superior performance compared to overlapping gene-based (OGB) and protein-protein interaction-based (PB) approaches.
Conclusions:
- PINTnet effectively identifies condition-specific perturbed pathways and their interactions, offering valuable insights into biological mechanisms.
- The developed method enhances pathway-level characterization by integrating topological and gene expression information.
- PINTnet is a valuable tool for systems biology research and is publicly available.