ABOUT RNALYTIX
Understanding the biology that current models miss
RNAlytiX is a University of Oxford and Imperial College London spinout in formation developing technologies for understanding hidden biological organisation within molecular systems.
We believe important biological information remains inaccessible to conventional analytical approaches — contributing to unexplained variability in disease, treatment response, and translational outcomes.
RNAlytiX will be formed to make that biology visible.
A knowledge company
RNAlytiX is not designed as a data-processing company.
It is designed as a knowledge company.
Our objective is not simply to analyse biological measurements, but to generate interpretable understanding of the biological mechanisms and organisational structures that shape cellular behaviour.
We believe future advances in medicine will come from deeper biological interpretation rather than larger datasets alone.
Mathematics for biology — not biology for AI
Modern AI has demonstrated extraordinary capabilities in pattern recognition and representation learning.
We embrace these mathematical advances.
However, our goal is different from building black-box prediction systems.
RNAlytiX develops approaches intended to preserve biological meaning and interpretability.
Our focus is explanation.
Because biology cannot remain a black box.
Scientists, clinicians, and therapeutic developers need understanding.
Our scientific philosophy
We believe that:
- Biological systems contain organisational structure that remains incompletely described.
- Important regulatory information exists beyond conventional abundance measurements.
- Clinical similarity can conceal biological diversity.
- Interpretation is becoming the central challenge of molecular medicine.
RNAlytiX will be built around these principles.
The Minds Behind RNAlytiX
RNAlytiX brings together expertise across mathematics, biology, computation, and translational science.
Our team combines experience from leading academic institutions with a shared ambition:
To uncover hidden biological intelligence and translate it into meaningful scientific and clinical impact.
Viktoriia Davletshyna
Operations & Translation
Professor Anastasia Papavasiliou
Computational Science
