About
A founder-led computational biology practice built around one principle: analysis you can inspect and explain.
Why Zenteomics exists
Proteomics datasets are difficult. Noise is high, batch effects are common, statistical assumptions are often violated quietly, and the gap between "we have data" and "we have a result we trust" is larger than most groups expect.
Zenteomics exists to close that gap — with careful analysis, honest QC, and documentation that survives peer review.
Every engagement is founder-led. No hand-offs to junior analysts. No boilerplate pipelines applied without judgment.
Operating principles
Explicit assumptions
Every analytical choice is documented. Assumptions are stated, not hidden.
Inspectable outputs
Deliverables are readable, reproducible, and auditable — not black boxes.
Scoped engagements
Each project has defined inputs, outputs, and boundaries. No scope drift.
Honest stage signaling
Zenteomics is early. That is stated directly, not obscured by enterprise language.