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.

For scalable insights, it integrates millions of transcriptomic datasets from public research, organized by:

  • Tissue type
  • Disease state
  • Treatment response

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:
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.

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