Identification of differentially expressed transcription factors in ovarian cancer
Ovarian cancer is the fifth most common form of cancer in women in the United States. Epithelial ovarian cancer is the most common and is highly lethal. In 2014, there will be an estimated 21,980 new cases and 14,270 deaths from ovarian cancer in the United States. No major strides have been made to improve survival over the past decade. Ovarian cancer is notable for initial chemotherapy sensitivity (>75% response rates) using combination platinum and taxane chemotherapy following debulking surg...
Provenance — who produced it, who reused it
Linked to 41 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.
- The m6A reader YTHDF1 promotes ovarian cancer progression via au... 2020 · 807 cites
- ELF3 is a negative regulator of epithelial-mesenchymal transitio... 2017 · 128 cites
- Integrated bioinformatics analysis for the screening of hub gene... 2020 · 110 cites
- Identification of differentially expressed genes and signaling p... 2018 · 86 cites
37 further papers cite 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
Scientific quality
Based on hands-on reproduction of the papers that use this dataset. A reproducible paper that stands on this data is positive evidence; a flagged one is a prompt to look closer — never a verdict on the dataset itself without the evidence.