ArticleScientific reports2018
A power law distribution of metabolite abundance levels in mice regardless of the time and spatial scale of analysis.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Unsupervised machine learning using an imaging mass spectrometry dataset automatically reassembles grey and white matter.Scientific reports · 2019Article
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5 authors.
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Abstract
Biomolecule abundance levels change with the environment and enable a living system to adapt to the new conditions. Although, the living system maintains at least some characteristics, e.g. homeostasis. One of the characteristics maintained by a living system is a power law distribution of biomolecule abundance levels. Previous studies have pointed to a universal characteristic of biochemical reaction networks, with data obtained from lysates of multiple cells. As a result, the spatial scale of the data related to the power law distribution of biomolecule abundance levels is not clear. In this study, we researched the scaling law of metabolites in mouse tissue with a spatial scale of quantification that was changed stepwise between a whole-tissue section and a single-point analysis (25 μm). As a result, metabolites in mouse tissues were found to follow the power law distribution independently of the spatial scale of analysis. Additionally, we tested the temporal changes by comparing data from younger and older mice. Both followed similar power law distributions, indicating that metabolite composition is not diversified by aging to disrupt the power law distribution. The power law distribution of metabolite abundance is thus a robust characteristic of a living system regardless of time and space.
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