Process / pipelineBioinformatics / omics

Time-Series Gene Set Enrichment Analysis — Dynamic Pathway Enrichment Across Time Points

Time-series gene set enrichment analysis (TS-GSEA) extends the classical GSEA framework to detect biologically coordinated gene sets — pathways, gene ontology terms, or curated signatures — whose collective expression changes meaningfully over time. Rather than comparing two snapshots, it models the full temporal trajectory of gene expression to identify which functional programs are activated, suppressed, or dynamically remodelled during a biological process such as development, treatment response, or disease progression.

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Sources

  1. Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., & Mesirov, J. P. (2005). Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences, 102(43), 15545–15550. DOI: 10.1073/pnas.0506580102
  2. Nueda, M. J., Tarazona, S., & Conesa, A. (2014). Next maSigPro: updating maSigPro bioconductor package for RNA-seq time series. Bioinformatics, 30(18), 2598–2602. DOI: 10.1093/bioinformatics/btu333

Related methods

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