Science
Inference generates hypotheses. Validation decides whether they were worth generating.
Cell-to-cell communication inference rests on openly published methods and reference resources. We think being precise about what those methods do, and do not, establish is a credibility asset, not a weakness.
What the method establishes
- Generate ranked, mechanistically-grounded hypotheses about which signaling axes differ between patient groups.
- Point to the specific cell states on each side of an interaction, rather than to a bulk tissue average.
- Narrow a genome-scale search space to a shortlist small enough to test experimentally.
What it does not
- Prove that an inferred interaction is physically occurring in the tissue.
- Establish causality, or that modulating a target will change a clinical outcome.
- Correct for confounders introduced by cohort composition, batch structure, or prior therapy.
Published foundations
The field we build on is in the open literature.
Methods for inferring signaling from single-cell and multi-modal measurements are actively published and openly licensed. We track this literature closely and cite it rather than paraphrasing it as our own.
Representative reference
Cell signaling pathways discovery from multi-modal data
He, Simpson et al. · bioRxiv preprint, 2025 · CC-BY 4.0
Read the preprintCited as relevant public literature. Cellazon claims no authorship of or exclusive rights to this work.
How we hold ourselves to it
One number matters more than the rest: how many candidates survive testing.
A pipeline that emits a hundred plausible targets is not a discovery engine. We design every engagement so that the shortlist is small, prespecified, and checked against orthogonal evidence, so the result is reportable whether or not it flatters us.
Discuss a validation plan