Open-source computational infrastructure for understanding, measuring and modeling biological aging.
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Updated
Nov 1, 2026 - Python
Open-source computational infrastructure for understanding, measuring and modeling biological aging.
🧬♻️ An AI-native, build-in-public compounding loop for aging science: falsifiable question → open data → public verifier → honest write-up → share → compound. No wet lab required.
Research checklists for published hiPSC maintenance, dual-SMAD, and GiWi protocols, with range checks and sterile gates.
Offline gravimetric flow analysis, independent-repeat uncertainty and drift diagnostics for research pumps.
Balanced optimal transport for cell-state snapshots, with auditable couplings and synthetic ambiguity benchmarks.
Open syringe-pump math, firmware, and a plunger carriage for in-vitro perfusion. The fluid path stays in the sterile syringe.
Group-aware baselines, leakage checks and reproducible reports for regenerative-medicine feature tables.
Brightfield colony and organoid morphology QC. Synthetic bake-off, retrainable logistic baseline. A contamination flag is triage, not a diagnosis.
Conservative spherical oxygen transport for organoid research, with analytic and nonlinear numerical verification.
Local Docker workbench for computational biology research and agent tools.
Control-gene module score for the published SenMayo gene set, with a size-matched random-set bake-off.
Closed-loop planner for in-vitro media factors. Expected improvement versus random search on a synthetic differentiation surface.
Source-traceable organoid mask measurement: object-level morphology, grouped instance agreement, frozen splits and hash-bound receipts. Geometry is not organoid health.
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