The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Combining genomics, metabolome analysis, and biochemical modelling to understand metabolic networks
Open accessAbstract
Now that complete genome sequences are available for a variety of organisms, the elucidation of gene functions involved in metabolism necessarily includes a better understanding of cellular responses upon mutations on all levels of gene products, mRNA, proteins, and metabolites. Such progress is essential since the observable properties of organisms – the phenotypes – are produced by the genotype in juxtaposition with the environment. Whereas much has been done to make mRNA and protein profiling possible, considerably less effort has been put into profiling the end products of gene expression, metabolites. To date, analytical approaches have been aimed primarily at the accurate quantification of a number of pre‐defined target metabolites, or at producing fingerprints of metabolic changes without individually determining metabolite identities. Neither of these approaches allows the formation of an in‐depth understanding of the biochemical behaviour within metabolic networks. Yet, by carefully choosing protocols for sample preparation and analytical techniques, a number of chemically different classes of compounds can be quantified simultaneously to enable such understanding. In this review, the terms describing various metabolite‐oriented approaches are given, and the differences among these approaches are outlined. Metabolite target analysis, metabolite profiling, metabolomics, and metabolic fingerprinting are considered. For each approach, a number of examples are given, and potential applications are discussed. Copyright © 2001 John Wiley & Sons, Ltd.
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A Mathematical Theory of Communication
Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb01338.x · Cited by 88,486
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Quantitative analysis of complex protein mixtures using isotope-coded affinity tags
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“Quantification of protein abundances can be performed using isotope coded affinity tags with precisions as accurate as 12% relative standard deviations [39], but to date, this technique has not been utilized for proteomic studies that go beyond one-to-one comparative experiments.”
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Cited by
Current approaches and challenges for the metabolite profiling of complex natural extracts
Wolfender, J.-L., Marti, G., Thomas, A., & Bertrand, S. (2015) · Journal of Chromatography A · doi:10.1016/j.chroma.2014.10.091 · Cited by 635
Unintended effects and their detection in genetically modified crops
Cellini, F., Chesson, A., Colquhoun, I., Constable, A., Davies, H. V., Engel, K. H., Gatehouse, A. M. R., Kärenlampi, S., Kok, E. J., Leguay, J.-J., et al. (2004) · Food and Chemical Toxicology · doi:10.1016/j.fct.2004.02.003 · Cited by 397
Metabolomics of a Superorganism
Goodacre, R. (2007) · The Journal of Nutrition · doi:10.1093/jn/137.1.259s · Cited by 225
Bujak, R., Daghir-Wojtkowiak, E., Kaliszan, R., & Markuszewski, M. J. (2016) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2016.00035 · Cited by 81
Metabolic profiling of residents in the vicinity of a petrochemical complex
Yuan, T.-H., Chung, M.-K., Lin, C.-Y., Chen, S.-T., Wu, K.-Y., & Chan, C.-C. (2016) · Science of The Total Environment · doi:10.1016/j.scitotenv.2016.01.033 · Cited by 31
Metadata
- Authors
- Fiehn, O.
- Venue
- Comparative and Functional Genomics
- Publisher
- Wiley
- Published
- 2001-06
- Volume
- 2
- Issue
- 3
- Pages
- 155-168
- ISSN
- 1531-6912 (ISSN-L)
- 1532-6268
- OpenAlex
- W2120714068
- Cited by
- 934
- References
- 4
- FWCI
- 5.43
- Type
- journal article
- Language
- en
- Open access
- bronze
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