Open-source constraint-based CDS design and pre-synthesis sequence review for plant CDS workflows, with primary support for Nicotiana benthamiana (Tobacco BY-2: experimental).
FactorForge performs deterministic CDS design with CAI/GC metrics, PolyA-signal screening, and Golden Gate/MoClo-aware checks. It is positioned as a pre-synthesis review harness: it helps teams generate reproducible CDS candidates, inspect assembly-relevant sequence constraints, and package design metadata before downstream synthesis, cloning, or experimental review. Primary support: N. benthamiana (agroinfiltration). Experimental host context: Tobacco BY-2 (--host by2).
FactorForge v3.5.4 uses independently versioned engines:
| Generation | Engine | Version | Availability |
|---|---|---|---|
| Gen 1 | Rule/profile | 1.0.0 | Stable, public |
| Gen 2 | DP v2 | 2.0.1 | Stable, public default feasibility path |
| Gen 2 | DP v2.1.1 | 2.1.1 | Explicit local-guard path; computational evidence only |
| Gen 3 | sLLM Hybrid | 0.2.0-preview.1 | Feature-gated constrained-generation research preview |
| Rescue | Adaptive partial DP | 1.0.0 | Exact suffix rescue conditioned on a verified prefix |
→ Full Documentation · Roadmap
pip install factorforge-cds
factorforge optimize my_protein.fasta -o output.fastaOr use the web app — no installation required.
| Method | Description | Link |
|---|---|---|
| Web App | No installation, demo & light use | factorforge.eijex.com |
| CLI / Python | Local use, batch processing, data privacy | pip install factorforge-cds |
| Docker | Full web interface locally | docker pull ghcr.io/eijex/factorforge-cds:latest |
| Eijex MCP | MCP-compatible agent access | mcp.eijex.com |
Experimental codon-distribution and evidence-ledger modules in the development checkout are scaffolds, not a validated laboratory policy or active learned recommendation service. Computational checks do not establish synthesis readiness or biological performance. Private inputs and collaborator packages must remain outside public repositories and dashboards.
The supported deterministic engines are the profile engine, stable DP v2, and the explicit DP v2.1.1 development candidate under:
src/factorforge/engines/profile/
src/factorforge/engines/dp_v2.py
src/factorforge/engines/dp_v2_1_1.py
src/factorforge/engines/sllm/
src/factorforge/discovery/
DP v2.1.1 adds an exact active-layer 5′ GC guard and Aho-Corasick rejection of homopolymers of 6 nt or longer to the v2.1 initiation-aware objective. It emits local-composition metrics and, when ViennaRNA and sufficient transcript context are available, a separately evaluated 5′ MFE value. It is not the default; its single-target calibration does not establish holdout generalization or biological performance.
The v3.5.x discovery-slate surface generates versioned Top-K research candidates, applies a shared deterministic hard-constraint filter, and records generator and fallback lineage. The sLLM path is disabled by default. A partial-DP rescue solves an exact suffix conditioned on the retained prefix; it is not a claim of global optimality and does not establish biological performance.
Historical implementation tracks are preserved under archive/ for provenance
and are not imported by the installed package or exposed as supported engines.
FactorForge outputs are in-silico only and have not been experimentally validated in wet-lab conditions. These checks support reviewability and reproducibility; they do not guarantee expression, yield, synthesis acceptance, folding, glycosylation, regulatory approval, or downstream biological performance. See Validation and VALIDATION.md.
FactorForge v3.5.4 (2026). Open-source constraint-based CDS design and sequence review.
Eijex. https://github.com/eijex/factorforge-cds
Mun-Kyu Kim (@eijex)
FactorForge design, CLI, Python API, and file export do not require a database. PostgreSQL persistence is an explicit Eijex integration path for retaining shared campaign and candidate identities; it is not enabled by default.
Install pip install "factorforge-cds[postgres]" only when using that integration.
The deployment must also provide a compatible eijex-db-core package and set
FACTORFORGE_DATABASE_URL. FactorForge contains no default database credentials and
does not silently fall back to another backend. See Persistence.
Explicit local SQLite research checkpoints in factorforge.db.connector remain a
separate local-only utility and are not the shared DBTL system of record.
GNU Affero General Public License v3.0 — see LICENSE.
Disclaimer: FactorForge is provided for research purposes only. Outputs are computational and have not been experimentally validated.
- Sponsor — Support our research via GitHub Sponsors or PayPal
- Docs — eijex.github.io/factorforge-cds
- Wet-lab Feedback — Public-safe feedback summaries are welcome via Share Wet-lab Feedback (GitHub). Do not submit raw sequences, confidential construct details, internal batch IDs, patient data, private contact information, exact process parameters, or confidential partner/customer data. Email
eijex.lab@gmail.comfor private or sensitive summaries. See VALIDATION.md before submitting. - Sequence Policy Profiles — FactorForge applies the sequence-review policy
chosen by the user; it does not define or approve a laboratory SOP. The web
app provides an illustrative YAML example and active-profile export.
Sequence-free, non-confidential suggestions can be submitted through the
public policy-template form; use
eijex.lab@gmail.comfor private or laboratory-specific profiles. See the sequence policy boundary. - GitHub Issues — bugs, features: github.com/eijex/factorforge-cds/issues
- Email — eijex.lab@gmail.com
- FactorForge — factorforge.eijex.com
- Eijex MCP — mcp.eijex.com
- Lab — www.eijex.com