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 v3.6.4 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
# Bioconda: Linux/macOS, or Ubuntu inside WSL on Windows
conda create -n factorforge-review --override-channels -c conda-forge -c bioconda --strict-channel-priority python=3.11 factorforge-cds
conda activate factorforge-review
# Via PyPI
pip install factorforge-cds
# Run optimization
factorforge optimize my_protein.fasta -o output.fastaOr use the web app — no installation required.
Bioconda does not support native Windows. Use WSL for that installation route; see installation and reviewer checks for the tested version, platform limitations and installed-package smoke command. Local DP optimization needs no Neon database, GCP account or GPU.
| Method | Description | Link |
|---|---|---|
| Bioconda | Linux/macOS; WSL on Windows | Isolated installation |
| 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 v3.6.4 (2026). Open-source constraint-based CDS design and sequence review.
Eijex. https://github.com/eijex/factorforge-cds
The v3.5.11 software archive and the accompanying computational preprint are separate citations. The preprint reports historical v3.2.0/v3.3.0 executions, not a benchmark of every later software release.
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.
The extra pins eijex-db-core==0.1.2. Supply its approved wheel bundle using
pip install --find-links PATH_TO_BUNDLE "factorforge-cds[postgres]"; the shared
package is not assumed to have been published on PyPI. Standalone installation
does not require it.
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
The web UI labels watermark as disabled and distinguishes the sequence-only baseline from retained experimental structure-conditioned testing. The local reviewed workflow supports 1DP-only or paired 3DP mode. General 3DP/4DP web access is paused by default; local research availability is not a biological-performance claim. See web UI boundaries.
The public form offers 1DP. General 3DP/4DP web access is paused pending evaluation and collaborator feedback. Research deployments require both a deliberate web build opt-in (ENABLE_EXPERIMENTAL_STRUCTURE_WEB) and server opt-in (FACTORFORGE_EXPERIMENTAL_3DP_ENABLED=true); these flags are availability controls, not authentication or research consent. Without the server flag, structure generation, recommendation and resolution requests fail with EXPERIMENTAL_STRUCTURE_DISABLED. Local experimental implementations are retained. See research boundaries.
Limits: 3–300 amino acids, structure content 250 KB, HTTP JSON body 1 MB. Both candidates use the configured codon reference, requested GC and canonical motif exclusions plus custom additions. Invalid inputs and infeasible candidates fail without a baseline fallback. Existing sequence-only settings and API requests remain supported. 3DP uses its explicit DP settings and does not apply Kozak, TpA, template or seed transformations. SOP checks are reported for both candidates; regeneration is manual and never silently changes mode. Watermark stays disabled.
This is stateless computational testing, with no external service dependencies or remote database recording. Those existing integrations remain available for later operational use. The structure file is not retained in the response or browser history; normal design results may be retained in local browser history. Submit only public-safe inputs. Structural conformity metrics are codon-weight proxies, not folding/expression measurements. These source changes are not deployed or a new package release.
Custom SOP management is paused. The built-in FactorForge default policy is applied; upload/export/preset/editing controls are hidden and disabled. Their code and previous browser configuration remain available for later reactivation through ENABLE_CUSTOM_SOP. Saved custom SOPs are ignored without deletion. 1DP remains active; general 3DP selection and API structure actions are disabled by default. Their retained research contract requires explicit deployment opt-in. This supersedes the earlier public SOP upload/export instructions.
Direct 1DP/3DP browser testing reports sense-CDS RNA motif scans and available initiation-window MFE in results, downloadable reports and local history. Structure confidence observations can suggest positions for explicit acceptance and review; unsupported inputs do not invent positions. These checks do not establish expression, yield or folding benefits. The default policy remains active and custom SOP management remains paused. See docs/experimental-structure.md for the API and measurement boundary.
factorforge nbfold annotate and factorforge nbfold optimize provide the experimental local Phase A/B workflow for exact-match structure files and an explicit user review manifest. See NB-Fold documentation.
Web structure handling now requires exact-match uploaded PDB/mmCIF coordinates and explicit reviewed positions. Automatic external folding, artificial structure/confidence fallback, and auto-approval are disabled. Structure metrics are synthetic reconstruction checks; independent public-structure/DSSP validation remains open.
factorforge.engines.stemcell_3dp.StemCell3DPOptimizer is a local experimental interface using a generic human-frequency reference and provisional Eijex review criteria. It is not an MSC/iPSC-calibrated model or a laboratory-approved SOP. See prototype boundaries. It is not a new production web host.
The opt-in Python DPV220Optimizer shares the v2.1.1 DP core and adds reviewed
position penalties. The experimental generic-human adapter uses this core;
existing plant web/NB-Fold routes retain their prior objective. See the
model card for usage, relaxation reporting and
engineering validation boundaries. This is not an expression or folding claim.