Raw Data

A study of 9 human subjects (7 male, 2 female, 24±1 years) investigated the influence of a single day of reduced physical activity on the skeletal muscle transcriptome and systemic metabolism surrounding an acute bout of aerobic exercise. The dataset includes RNAseq data from muscle biopsies taken before and 4-hours post-exercise, respiratory gas exchange analysis, and blood metabolite measurements. It was authored by Kevin Gries and last updated on 2026-04-29.

Use Cases

• Analyzing differential gene expression in skeletal muscle based on RNAseq data before and after exercise.
• Investigating the interaction between physical activity levels and metabolic fuel utilization based on respiratory exchange ratio and carbohydrate use data.
• Studying the impact of short-term inactivity on systemic metabolite levels, such as triglycerides, measured in blood samples.

Strengths

• Includes multi-modal data: RNAseq transcriptomics, respiratory gas exchange, and blood metabolite measurements.
• Utilizes a controlled crossover design with two activity conditions (normal and reduced steps).
• Data is associated with a specific, peer-reviewed study protocol described in the summary.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is small (135.8 KB), indicating a limited scope, likely focused on summary or processed results rather than raw sequencing reads.

Provenance

Source

Kevin Gries via figshare

Collection Method

Data collected from a human subject crossover study involving exercise trials, muscle biopsies, and blood sampling.

Freshness

Last updated 2026-04-29 20:49:20; freshness should be verified.