SBV - Gene Expression Profiles of Lung Cancer Tumors - Adenocarcinomas and Squamous Cell Carcinomas
This dataset encompassing the profiles of 150 lung cancer tumors was developed to serve as test dataset in the SBV IMPROVER Diagnostic Signature Challenge (sbvimprover.com). The aim of this subchallenge was to verify that it is possible to extract a robust diagnostic signature from gene expression data that can identify stages of different types of lung cancer. Participants were asked to develop and submit a classifier that can stratify lung cancer patients in one of four groups – Stage 1 of Ade...
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.
- Robust meta-analysis of gene expression using the elastic net 2015 · 183 cites
- EMT is associated with an epigenetic signature of ECM remodeling... 2019 · 148 cites
- Strengths and limitations of microarray-based phenotype predicti... 2013 · 123 cites
- Macrophage-Related SPP1 as a Potential Biomarker for Early Lymph... 2021 · 111 cites
- FBXO11 promotes ubiquitination of the Snail family of transcript... 2015 · 83 cites
- Eight potential biomarkers for distinguishing between lung adeno... 2017 · 74 cites
26 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