Process / pipelineBioinformatics / omics

Time-Series Pathway Enrichment Analysis — Dynamic Pathway Activity Over Time

Time-series pathway enrichment analysis identifies biological pathways whose coordinated gene activity changes significantly across ordered time points. Rather than treating each time point independently, the method models the temporal trajectory of gene expression within each pathway and tests whether entire biological programs — not just individual genes — are activated or suppressed in a time-dependent manner. It is widely used in developmental biology, drug response studies, and infection time courses.

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Sources

  1. Ernst, J., Nau, G. J., & Bar-Joseph, Z. (2005). Clustering short time series gene expression data. Bioinformatics, 21(Suppl 1), i159–i168. link
  2. Cheng, J., Tegge, A. N., & Bhatt, D. L. (2014). A method for identifying and interpreting time-series pathway activity changes from gene expression data. Bioinformatics, 30(21), 3147–3154. link

Related methods

ScholarGateTime-series pathway enrichment analysis (Time-Series Pathway Enrichment Analysis). Retrieved 2026-06-04 from https://scholargate.app/en/bioinformatics/time-series-pathway-enrichment-analysis