Breast Cancer Dataset
Signatures of Oncogenic Pathway Deregulation in Human Cancers. The ability to define cancer subtypes, recurrence of disease, and response to specific therapies using DNA microarray-based gene expression signatures has been demonstrated in multiple studies. Such data is also of substantial importance to the analysis of cellular signaling pathways central to the oncogenic process. With this focus, we have developed a series of gene expression signatures that reliably reflect the activation status...
Provenance — who produced it, who reused it
Linked to 25 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.
- Wild-type p53 upregulates an early onset breast cancer-associate... 2018 · 539 cites
- A Three-Gene Model to Robustly Identify Breast Cancer Molecular... 2012 · 328 cites
- bc-GenExMiner 3.0: new mining module computes breast cancer gene... 2013 · 277 cites
- A network module-based method for identifying cancer prognostic... 2012 · 165 cites
- Downregulation of long noncoding RNA MALAT1 induces epithelial-t... 2015 · 151 cites
- BreastMark: An Integrated Approach to Mining Publicly Available... 2013 · 143 cites
- De-Differentiation Confers Multidrug Resistance Via Noncanonical... 2014 · 114 cites
- Systematic Analysis of Gene Expression Alteration and Co-Express... 2018 · 84 cites
17 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
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently