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02 — Map

Turn multi-omic EV observations into tissue-anchored, testable biological programs.

  • Research Program
  • 3M framework
  • Interpretable multi-omics, biological calibration, and evidence-backed hypothesis generation.
The question

Which molecular programs track progression—and what CNS biology could explain them?

Interpretable multi-omics, biological calibration, and evidence-backed hypothesis generation.

From features to programs

The objective is not a black-box score. Models are organized around coherent miRNA, mRNA, protein, imaging, and clinical relationships so that a candidate signature can be traced back to pathways, cell contexts, and experimental questions.

Loss of coordination across regulatory and effector molecular programs

A working hypothesis is that disease progression may involve a loss of coordination across regulatory and effector molecular programs. Mapping asks where that coordination changes, whether it is robust across cohorts, and whether it is biologically plausible.

A model must explain its route back to biology

The analytical workflow uses program-level relationships rather than isolated rankings: quality-controlled molecular inputs, cohort-aware model development, biologically interpretable features, tissue and cell-context anchoring, and a locked evaluation plan for the next cohort.

Multi-omic measurements aligned with tissue and cell context.
Multi-omic learning schematicMap connects molecular layers to tissue and cell context, preserving the evidence trail from cargo observation to an interpretable biological program and a testable next experiment.