Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uchambuzi wa Proteomiki× | Uchambuzi wa Metabolomics× | |
|---|---|---|
| Nyanja | Bioinformatiki | Bioinformatiki |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1994–2003 (term coined 1994; shotgun proteomics established early 2000s) | 1998–2002 |
| Mwanzilishi≠ | Marc Wilkins, Matthias Mann, Ruedi Aebersold (proteome/mass spectrometry foundations) | Oliver et al. (coining of 'metabolomics'); Oliver Fiehn (systematic framework) |
| Aina | Quantitative omics pipeline | Quantitative omics pipeline |
| Chanzo asilia≠ | 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. link ↗ | Fiehn, O. (2002). Metabolomics — the link between genotypes and phenotypes. Plant Molecular Biology, 48(1-2), 155–171. link ↗ |
| Majina mbadala | proteomics, mass spectrometry-based proteomics, shotgun proteomics, quantitative proteomics | metabolome profiling, metabolic profiling, metabonomics, metabolite profiling |
| Zinazohusiana | 6 | 6 |
| Muhtasari≠ | 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. |
| ScholarGateSeti ya data ↗ |
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