পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| টাইম-সিরিজ পাথওয়ে এনরিচমেন্ট বিশ্লেষণ× | পাথওয়ে এনরিচমেন্ট বিশ্লেষণ× | |
|---|---|---|
| ক্ষেত্র | জৈব তথ্যবিজ্ঞান | জৈব তথ্যবিজ্ঞান |
| পরিবার | Process / pipeline | Process / pipeline |
| উদ্ভবের বছর≠ | 2005–2014 | 2003–2005 |
| প্রবর্তক≠ | Bar-Joseph and colleagues (temporal gene expression); extended by Cheng, Bhatt et al. for pathway-level time-series inference | Mootha et al. (2003); systematised by Subramanian et al. (2005) |
| ধরন≠ | Functional enrichment analysis with temporal modeling | Statistical functional annotation method |
| মৌলিক উৎস≠ | Ernst, J., Nau, G. J., & Bar-Joseph, Z. (2005). Clustering short time series gene expression data. Bioinformatics, 21(Suppl 1), i159–i168. link ↗ | 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 ↗ |
| অপর নাম | temporal pathway analysis, longitudinal pathway enrichment, dynamic pathway analysis, TPEA | PEA, overrepresentation analysis, ORA, functional enrichment analysis |
| সম্পর্কিত≠ | 5 | 6 |
| সারসংক্ষেপ≠ | 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. | Pathway enrichment analysis (PEA) is a statistical approach that takes a list of genes or proteins of interest — typically derived from a differential expression or proteomics experiment — and identifies which pre-defined biological pathways or functional gene sets are represented more often than expected by chance. By mapping individual molecular changes onto curated pathway knowledge bases such as KEGG, Gene Ontology, or Reactome, PEA translates long gene lists into interpretable biological processes, making it a central tool in the post-analysis of high-throughput omics experiments. |
| ScholarGateডেটাসেট ↗ |
|
|