Reproducible plant CDS design,
powered by DBTL.
Connecting computational plant sequence engineering with reviewable wet-lab evidence capture.
Open-source, constraint-aware, and citable.
pip install factorforge-cdsconda install factorforge-cdssoondocker pull ghcr.io/eijex/factorforge-cds:latesteijex builds reproducible, evidence-linked software infrastructure for plant molecular expression — open-source where possible, evidence-bounded by design, and freely available to the research community.
DBTL Platform Objective
End-to-End DBTL Infrastructure for Plant Expression.
Eijex provides a closed-loop Design–Build–Test–Learn (DBTL) platform for plant molecular expression research. We connect open-source, constraint-aware CDS design (FactorForge) to wet-lab validation data capture (ValidationHub) and machine-learning yield optimization (YieldPredict).
Every step is intentionally evidence-bounded: computational CDS outputs support expert review prior to synthesis, cloning, and experimental testing, ensuring reproducible research decisions.
Capability roadmap
- 1Reproducible CDS design and reviewable sequence-analysis artifacts
- 2Benchmark governance with explicit evidence boundaries
- 3Pre-synthesis review harnesses for synthesis, cloning, and experimental planning
- 4Validation-data capture, audit trails, and documented research decisions
- 5Human-supervised AI-assisted Design-Build-Test-Learn workflows
Products
Tools built for the bench and the pipeline.
FactorForge
CDS Design Review
Pre-synthesis sequence review for plant CDS workflows. Generates reproducible CDS candidates and reviews CAI, GC%, configured sequence motifs, and assembly-relevant restriction-site conflicts.
pip install factorforge-cds