Systematic identification of metabolites controlling gene expression in E. coli
Cellular metabolism controls gene expression through allosteric interactions between metabolites and transcription factors. Methods to detect these regulatory interactions are mostly based on in vitro binding assays, but there are no methods to identify them at a genome-scale in vivo. Here we show that dynamic transcriptome and metabolome data identify metabolites that are potential effectors of transcription factors in E. coli. By switching the culture conditions between starvation and growth f...
Provenance — who produced it, who reused it
Linked to 2 papers in the literature. Roles are inferred factual signals (who deposited the data vs who reused it), with counts — never a judgement about any author.
- Systematic identification of metabolites controlling gene expres... 2019 · 122 cites
1 further paper cites this accession but reuse could not be confirmed.
Deep data QC
metadata only · no data-level QC for this typeStandardized, field-standard QC computed by touching the data — every metric states how it was obtained
No quantitative QC rubric exists for this data type yet, so it is deliberately left unscored — this is an honest "not applicable", not a poor rating.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently