Predicting age from the transcriptome of human dermal fibroblasts
There is a marked heterogeneity in human lifespan and health outcomes for people of the same chronological age. Thus, one fundamental challenge is to identify molecular and cellular biomarkers of aging that could predict lifespan and be useful in evaluating lifestyle changes and therapeutic strategies in the pursuit of healthy aging. Here, we developed a computational method to predict biological age from gene expression data in skin fibroblast cells using an ensemble of machine learning classif...
Provenance — who produced it, who reused it
Linked to 16 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.
- Multi-omic rejuvenation of human cells by maturation phase trans... 2022 · 176 cites
- BiT age: A transcriptome‐based aging clock near the theoretical... 2021 · 172 cites
- Phosphorylated Lamin A/C in the Nuclear Interior Binds Active En... 2020 · 116 cites
- Landscape of adenosine-to-inosine RNA recoding across human tiss... 2022 · 103 cites
- Repetitive elements as a transcriptomic marker of aging: Evidenc... 2020 · 89 cites
- mitoXplorer, a visual data mining platform to systematically ana... 2019 · 87 cites
- Epigenetic deregulation of lamina-associated domains in Hutchins... 2020 · 77 cites
8 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.