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MetabolomicsMetabolomic correlation-network modules in Arabidopsis based on a graph-clustering approach
Deciphering the metabolome is essential for a better understanding of the cellular metabolism as a system. Typical metabolomics data show a few but significant correlations among metabolite levels when data sampling is repeated across individuals grown under strictly controlled conditions. Although ...
2014-03-01 | MTBLS45 | MetaboLights
MetabolomicsUnbiased characterization of genotype-dependent metabolic regulations by metabolomic approach in Arabidopsis thaliana
Metabolites are not only the catalytic products of enzymatic reactions but also the active regulators or the ultimate phenotype of metabolic homeostasis in highly complex cellular processes. The modes of regulation at the metabolome level can be revealed by metabolic networks. We investigated the me...
2014-03-01 | MTBLS40 | MetaboLights
MetabolomicsCreating a Reliable Mass Spectral–Retention Time Library for All Ion Fragmentation-Based Metabolomics

Accurate metabolite identification remains one of the primary challenges in a metabolomics study. A reliable chemical spectral library increases the confidence in annotation, and the availability of raw and annotated data in public databases facilitates the transfer of Liquid chromatography coupl...

2019-10-30 | MTBLS1040 | MetaboLights
MetabolomicsCorrelation-based Deconvolution (CorrDec) to generate high quality MS2 spectra from data independent acquisition in multi-sample studies (Chemical standards assay)

Data-independent acquisition mass spectrometry (DIA-MS) is essential for information-rich spectral annotations in untargeted metabolomics. However, the acquired MS2 spectra are highly complex, posing significant annotation challenges. We have developed a correlation-based deconvolution (CorrDec) ...

2020-07-13 | MTBLS787 | MetaboLights
MetabolomicsCorrelation-based Deconvolution (CorrDec) to generate high-quality MS2 spectra from data-independent acquisition in multi-sample studies (Urine assay)

Data-independent acquisition mass spectrometry (DIA-MS) is essential for information-rich spectral annotations in untargeted metabolomics. However, the acquired MS2 spectra are highly complex, posing significant annotation challenges. We have developed a correlation-based deconvolution (CorrDec) ...

2020-07-13 | MTBLS816 | MetaboLights
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