Predicting Features of Breast Cancer with Gene Expression Patterns
Predictors built from gene expression data accurately predict ER, PR, and HER2 status, and divide tumor grade into high-grade and low-grade clusters; intermediate-grade tumors are not a unique group. In contrast, gene expression data cannot be used to predict tumor size or lymphatic-vascular invasion.
Provenance — who produced it, who reused it
Linked to 40 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.
- A Three-Gene Model to Robustly Identify Breast Cancer Molecular... 2012 · 328 cites
- Amplification and high-level expression of heat shock protein 90... 2012 · 183 cites
- Actin stress fiber organization promotes cell stiffening and pro... 2017 · 182 cites
- DEAD-box helicase DP103 defines metastatic potential of human br... 2014 · 131 cites
- Cancer-associated fibroblasts facilitate premetastatic niche for... 2022 · 131 cites
- Metastasis-suppressor transcript destabilization through TARBP2... 2014 · 101 cites
- The Lineage Determining Factor GRHL2 Collaborates with FOXA1 to... 2019 · 92 cites
- Concurrent Gene Signatures for Han Chinese Breast Cancers 2013 · 84 cites
- Cyclin D1 induction of Dicer governs microRNA processing and exp... 2013 · 74 cites
- SPHK1 regulates proliferation and survival responses in triple-n... 2014 · 73 cites
30 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