| Literature DB >> 26371234 |
Takayuki Tohge1, Federico Scossa2, Alisdair R Fernie2.
Abstract
Huge insight into molecular mechanisms and biological network coordination have been achieved following the application of various profiling technologies. Our knowledge of how the different molecular entities of the cell interact with one another suggests that, nevertheless, integration of data from different techniques could drive a more comprehensive understanding of the data emanating from different techniques. Here, we provide an overview of how such data integration is being used to aid the understanding of metabolic pathway structure and regulation. We choose to focus on the pairwise integration of large-scale metabolite data with that of the transcriptomic, proteomics, whole-genome sequence, growth- and yield-associated phenotypes, and archival functional genomic data sets. In doing so, we attempt to provide an update on approaches that integrate data obtained at different levels to reach a better understanding of either single gene function or metabolic pathway structure and regulation within the context of a broader biological process.Mesh:
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Year: 2015 PMID: 26371234 PMCID: PMC4634077 DOI: 10.1104/pp.15.01006
Source DB: PubMed Journal: Plant Physiol ISSN: 0032-0889 Impact factor: 8.340