So sánh phương pháp

	Phân tích Proteomics	Phân tích Chuyển hóa
Lĩnh vực	Tin sinh học	Tin sinh học
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1994–2003 (term coined 1994; shotgun proteomics established early 2000s)	1998–2002
Người khởi xướng	Marc Wilkins, Matthias Mann, Ruedi Aebersold (proteome/mass spectrometry foundations)	Oliver et al. (coining of 'metabolomics'); Oliver Fiehn (systematic framework)
Loại	Quantitative omics pipeline	Quantitative omics pipeline
Công trình gốc	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.	Fiehn, O. (2002). Metabolomics — the link between genotypes and phenotypes. Plant Molecular Biology, 48(1-2), 155–171.
Tên gọi khác	proteomics, mass spectrometry-based proteomics, shotgun proteomics, quantitative proteomics	metabolome profiling, metabolic profiling, metabonomics, metabolite profiling
Liên quan	6	6
Tóm tắt	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.	Metabolomics analysis is the large-scale, systematic measurement of small-molecule metabolites in a biological sample to characterise the metabolome — the complete set of metabolic intermediates and products present under defined conditions. By coupling high-throughput analytical platforms such as mass spectrometry (MS) or nuclear magnetic resonance (NMR) spectroscopy with multivariate statistics and pathway databases, metabolomics bridges the genotype–phenotype gap and captures the downstream functional output of genes, transcripts, and proteins in real time.