Corpus 1,272 assessed · 1,173 scored · 643 reproduced ≥75 · 168 flagged ·∅ 74.1/100
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GSE111936

GEO first seen 2018

Comprehensive, high-resolution binding energy landscapes reveal context dependencies of transcription factor binding

Organism
synthetic construct
Samples
14
Type
Other
Submitted
2018-03-16

Transcription factors (TFs) are primary regulators of gene expression in cells, where they bind specific genomic target sites to control transcription. Quantitative measurements of TF-DNA binding energies can improve the accuracy of predictions of TF occupancy and downstream gene expression in vivo and shed light on how transcriptional networks are rewired throughout evolution. Here, we present a novel sequencing-based TF binding assay and analysis pipeline (BET-seq, for Binding Energy Topograph...

Provenance — who produced it, who reused it

Linked to 1 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.

Deposited / produced by
Polly M Fordyce
Reused by

Deep data QC

metadata only · no data-level QC for this type

Standardized, 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.

QC cost 22 s compute

measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently