Metabolomics in systems biology.

By Wolfram Weckwerth. Annual Review of Plant Biology, 2003

722 citations recorded by the source corpus.

The primary aim of "omic" technologies is the nontargeted identification of all gene products (transcripts, proteins, and metabolites) present in a specific biological sample. By their nature, these technologies reveal unexpected properties of biological systems. A second and more challenging aspect of omic technologies is the refined analysis of quantitative dynamics in biological systems. For metabolomics, gas and liquid chromatography coupled to mass spectrometry are well suited for coping with high sample numbers in reliable measurement times with respect to both technical accuracy and the identification and quantitation of small-molecular-weight metabolites. This potential is a prerequisite for the analysis of dynamic systems. Thus, metabolomics is a key technology for systems biology. The aim of this review is to (a) provide an in-depth overview about metabolomic technology, (b) explore how metabolomic networks can be connected to the underlying reaction pathway structure, and (c) discuss the need to investigate integrative biochemical networks.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/bd7eb46b953c9b97ec64f7efe1fa05483751a3b3

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Citations in the corpus

Metabolite profiling: from diagnostics to systems biology (2004, background): “, they are also beginning to include metabolite- and pharmaceutical-based approache”
Multivariate Analysis in Metabolomics. (2012, background): “” Such a definition implies that metabolomic studies offer the finest-grained detail available in the nascent field of systems biology: a molecular-level convolution of all upstream genomic, transcriptomic and proteomic responses of an organism to a given stimulus or change [2-4].”
Correlative GC-TOF-MS-based metabolite profiling and LC-MS-based protein profiling reveal time-related systemic regulation of metabolite–protein networks and improve pattern recognition for multiple biomarker selection (2005, methodology): “This holds especially true when profiling plant tissues, where the harvesting process and sample preparation must be tightly controlled to ensure high accuracy (Weckwerth, 2003).”
RIKEN tandem mass spectral database (ReSpect) for phytochemicals: a plant-specific MS/MS-based data resource and database. (2012, background): “Metabolomics is an ‘‘omics’’ approach to the investigation of metabolites present in biological samples (Fernie et al., 2004; Weckwerth, 2003).”
Mass spectrometry-based metabolomics. (2007, background): “Up to 200,000 metabolites can be encountered in the plant kingdom (Weckwerth, 2003).”
VANTED: A system for advanced data analysis and visualization in the context of biological networks (2006, background): “These findings are consistent with another study in which it has been shown that glucose and mannitol are negatively correlated to a highly connected amino acid cluster [35].”
Observing and Interpreting Correlations in Metabolic Networks (2003, background): “Metabolomic analysis aims at the unbiased identificati on and quantification of all metabolites in a biological sample [1, 3, 5, 7 ]. By integrating the data obtained from such large-sc ale experiments into metabolic correlation networks, its powe r to significantly extend and enhance existing func”
Metabolomics by numbers: acquiring and understanding global metabolite data. (2004, background): “‘Systems biology’ describes a range of techniques, including the ‘omics and mathematical modelling, for understanding systems ‘as a whole’ [63,64], and it is widely recognized that metabolomics will have a major part to play in its development [ 65 ].”
Flux balance analysis in the era of metabolomics (2006, background): “This is mainly attributable to the fact that many metabolites are found at very low concentrations, which necessitates additional technology development [3, 4, 12].”