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Inferring metabolic rewiring in embryonic neural development using single cell data
[article]
2020
bioRxiv
pre-print
Metabolism is intricately linked with cell fate changes. Much of this understanding comes from detailed metabolomics studies averaged across a population of cells which may be composed of multiple cell types. Currently, there are no quantitative techniques sensitive enough to assess metabolomics broadly at the single cell level. Here we present scMetNet, a technique that interrogates metabolic rewiring at the single cell resolution and we apply it to murine embryonic development. Our method
doi:10.1101/2020.09.03.282442
fatcat:5cs35vlvpzeang2ct33ev4t5jq