Krahasoni metodat

	Analiza Proteomike	Analiza e Pasurimit të Grupeve Gjenetike (GSEA)
Fusha	Bioinformatikë	Bioinformatikë
Familja	Process / pipeline	Process / pipeline
Viti i origjinës	1994–2003 (term coined 1994; shotgun proteomics established early 2000s)	2005 (seminal PNAS paper; predecessor concept in Mootha et al. 2003)
Krijuesi	Marc Wilkins, Matthias Mann, Ruedi Aebersold (proteome/mass spectrometry foundations)	Aravind Subramanian, Pablo Tamayo, Vamsi K. Mootha, Jill P. Mesirov, Todd R. Golub, Eric S. Lander et al. (Broad Institute)
Lloji	Quantitative omics pipeline	Functional genomics / enrichment analysis
Burimi themelues	Wilkins, M. R., Sanchez, J.-C., Gooley, A. A., Appel, R. D., Humphery-Smith, I., Hochstrasser, D. F., & Williams, K. L. (1996). Progress with proteome projects: Why all proteins expressed by a genome should be identified and how to do it. Biotechnology and Genetic Engineering Reviews, 13(1), 19–50.	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.
Emërtime të tjera	proteomics, mass spectrometry-based proteomics, shotgun proteomics, quantitative proteomics	GSEA, gene-set analysis, functional enrichment analysis, pathway-level enrichment
Të lidhura	6	5
Përmbledhja	Proteomics analysis is a systematic pipeline for identifying and quantifying proteins in biological samples using mass spectrometry. Starting from raw spectral data, the workflow searches protein sequence databases, estimates abundance across conditions, applies statistical tests for differential expression, and maps findings onto biological pathways. It complements transcriptomics by capturing post-translational regulation and actual protein abundance, and is central to biomarker discovery, drug-target identification, and systems biology.	Gene Set Enrichment Analysis (GSEA) is a computational method that determines whether a predefined set of genes — representing a biological pathway, process, or function — shows statistically significant, coordinated differences between two biological conditions. Unlike simple fold-change filtering, GSEA operates on all measured genes ranked by a correlation metric, detecting subtle but consistent shifts across an entire pathway even when no single gene passes a significance threshold.