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Resveratrol Diet Aging (Heart, Liver, Muscle and Fat Tissue)

GSE11845 Mus musculus (mouse) Expression microarray 150 samples Submitted 2008/08/05 Platform GPL6103
At a glance

Expression microarray · mouse · 150 samples

What it is
Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism
Mus musculus (mouse)
Samples
150 samples: 150 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed expression table (series matrix) and the array files, from NCBI.
Summary (written by the submitters)
Resveratrol delays age-related deterioration and mimics transcriptional aspects of dietary restriction without extending lifespan A small molecule that safely mimics the ability of dietary restriction (DR) to delay age-related diseases in laboratory animals is greatly sought after. We and others have shown that resveratrol mimics effects of DR in lower organisms.
Read the full summary ↓
In mice, we find that resveratrol induces gene expression patterns in multiple tissues that parallel those induced by DR and every-other-day feeding. Moreover, resveratrol-fed elderly mice shows a marked reduction in signs of aging including reduced albuminuria, decreased inflammation and apoptosis in the vascular endothelium, increased aortic elasticity, greater motor coordination, reduced cataract formation, and preserved bone mineral density. However, mice fed a standard diet did not live longer when treated with resveratrol beginning at mid-life. Our findings indicate that resveratrol treatment has a range of beneficial effects in mice but does not increase the longevity of ad libitum-fed animals when started mid-life.
This dataset
Open GSE11845 in finder → Find more mouse microarray datasets →
Download · which file do I need?

Direct links to NCBI, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need.

All supplementary files ↗
3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE11845_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

What the files usually look like: For arrays the series matrix is normally the normalised expression table you want; the raw array files (CEL and similar) are in the RAW.tar.

Also filed as BioProject PRJNA105639. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 18599363) ↗
Study design
150 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 150 sample titles: 150 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 110 more — browse all 150 samples with per-sample file links →

Datasets on a similar topic

Search all mouse microarray datasets in GEO →

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