The project
Gravity, Disease and RNA: An AI Study in Mice and Humans
Alicia’s project brings together machine learning and biology to investigate how gene activity changes under different conditions. Her analysis draws on public datasets covering spaceflight, ageing, reduced movement and muscle loss.
Working with Dr Max Patacchiola, she is reproducing an existing published analysis and extending it with comparisons across mouse and human datasets. A central question is whether patterns identified in mice also help explain human sarcopenia, the loss of muscle associated with ageing.
How the project took shape
Reproduce the research
Recreate a published analysis, compare the results with the original work and examine how implementation choices affect the findings.
Compare biological patterns
Use dimensionality reduction and statistical comparisons to investigate gene-expression patterns across species and conditions.
Test the evidence
Evaluate models with cross-validation and examine uncertainty, sample sizes and the limits of transferring findings between datasets.
Project outcomes
- Reproduced key statistical results from the original published analysis.
- Extended the investigation to multiple mouse and human datasets, including three human sarcopenia cohorts.
- Developed a comparative analysis that examines both model performance and the uncertainty in the findings.
The research is ongoing. Preliminary analyses highlight the importance of sample size and careful validation; a scientific paper is the intended next outcome.
