Gene expression profiles of serous ovarian cancer samples
To elucidate the mechanisms of rapid progression of serous ovarian cancer, gene expression profiles from forty-three ovarian cancer tissues comprising eight early stage and thirty-five advanced stage tissues were performed using oligonucleotide microarrays of 18,716 genes. By non-negative matrix factorization analysis using 178 genes, which were extracted as stage-specific genes, 35 advanced-stage cases were classified into two subclasses with superior (n = 17) and poor (n = 18) outcome evaluat...
Provenance — who produced it, who reused it
Linked to 32 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.
- curatedOvarianData: clinically annotated data for the ovarian ca... 2013 · 213 cites
- Dysregulation of pseudogene/lncRNA-hsa-miR-363-3p-SPOCK2 pathway... 2019 · 104 cites
- EZH2-mediated epigenetic silencing of TIMP2 promotes ovarian can... 2017 · 88 cites
29 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.