DINA
Our Core Intelligence
Mavatar’s platform features DINA (Deep Integrated Network Analysis)
a framework built on two decades of research in genomics and bioinformatics.
HIGH-RESOLUTION INSIGHTS
DINA Makes Sense of Biomedical Data
DINA helps make sense of fragmented biomedical data.
It integrates millions of transcriptomic datasets from public research,
organized by:
- Tissue type
- Disease state
- Treatment response
for scalable insights.
FULLY DATA-DRIVEN FRAMEWORK
What Makes DINA Different?
DINA is a data-driven framework designed to uncover patterns and relationships not yet reflected in literature or guidelines.
Its key pillars include:
Its key pillars include:
SCALE
All Cells. All Genes.
All Diseases.
DINA maps the interactions of 22,000 genes across all known tissues and conditions—offering a systems-level understanding of disease biology.
DISCOVERY
Cross-Disease,
Tissue-Specific Discovery
The framework learns from thousands of disease contexts simultaneously, identifying both shared and distinct molecular mechanisms within specific tissues.
INSIGHT
Unbiased Insight Generation
DINA integrates data from humans, cell lines, animal models, and clinical trials—free from prior assumptions—allowing for novel insights into pathogenesis, drug response, and disease variability.
USING DIGITAL TWINS
Precision at Scale
DINA enables the creation of digital twins for diseases and patients. These detailed representations allow exploration of therapy interactions with disease mechanisms.
Our AI algorithms identify links between:
- Gene networks
- Pathways
- Drug targets
Aiding treatment strategy and translational research.
SCIENTIFIC RIGOR
AI with Purpose
While many tools rely on black-box generative AI, Mavatar does not. We use machine learning specifically designed for high-integrity, large-scale biomedical analysis—ensuring transparency, interpretability, and scientific rigor at every step.