| # Reconstructing the BioCandidateRanker training corpus |
|
|
| This guide rebuilds the exact development corpus, frozen split, and baseline |
| evaluation from the public upstream source plus the artifacts in this repository. |
| It never requires the measurement rows to pass through this dataset repository. |
|
|
| ## 1. Obtain the original corpus |
|
|
| Download `Kcat_combination_0918_wildtype_mutant.json` from the original |
| [UniKP repository](https://github.com/Luo-SynBioLab/UniKP). The same wildtype+mutant |
| kcat compilation was distributed with DLKcat |
| ([Zenodo record 6438262](https://zenodo.org/records/6438262)). |
|
|
| ## 2. Verify the frozen identity |
|
|
| The project's frozen manifests pin the source bytes. Compute: |
|
|
| ```bash |
| sha256sum Kcat_combination_0918_wildtype_mutant.json |
| ``` |
|
|
| Expected: |
|
|
| ``` |
| 13643b0b36374f8d3f64d8b014882cf1b3b58946eeaae2b9dcd59e8b2c2d6719 (12,132,719 bytes, 17,010 rows) |
| ``` |
|
|
| If the hash differs, stop: the split assignments in `data/homology_split.parquet` |
| are keyed by row index and are only valid for a byte-identical copy. Cross-check |
| against `configs/unikp_source_manifest.json` and `data/unikp_audit.json` in this |
| repository. A verified copy was confirmed on 2026-10-24. |
|
|
| ## 3. Audit the corpus with the project CLI |
|
|
| Unpack `release/software-implementation-v10-redacted.zip`, then: |
|
|
| ```powershell |
| python -m venv .venv |
| .\.venv\Scripts\python.exe -m pip install -e ".[dev]" |
| $env:PYTHONPATH="src" |
| python -m biocandidate.cli audit-data ` |
| --data "<path>\Kcat_combination_0918_wildtype_mutant.json" ` |
| --output artifacts\unikp_audit.json |
| ``` |
|
|
| Expected adapter statistics (recorded in `configs/unikp_source_manifest.json`): |
|
|
| | field | value | |
| |---|---| |
| | total rows | 17,010 | |
| | accepted | 16,838 | |
| | duplicates | 395 | |
| | conflicting duplicates | 215 | |
| | rejected | 172 | |
|
|
| ## 4. Apply the frozen homology-cold split |
|
|
| The split in `data/homology_split.parquet` / `data/homology_split.json` maps each |
| 0-based `source_row` to an MMseqs2 cluster and a partition (MMseqs2 `linclust`, |
| min identity 0.3, coverage 0.8, coverage mode 0, seed 42; 2,204 clusters; |
| 13,470 / 1,684 / 1,684 rows). Join it to the source file by row index: |
|
|
| ```python |
| import json |
| import pandas as pd |
| |
| source = json.load(open("Kcat_combination_0918_wildtype_mutant.json", encoding="utf-8")) |
| split = pd.read_parquet("data/homology_split.parquet").set_index("source_row") |
| train = [source[i] for i in split.index[split["split"] == "train"]] |
| ``` |
|
|
| Or let the CLI bind the identity itself (recommended — it refuses a source that |
| does not match the audit manifest): |
|
|
| ```powershell |
| python -m biocandidate.cli train ` |
| --data "<path>\Kcat_combination_0918_wildtype_mutant.json" ` |
| --manifest artifacts\unikp_audit.json ` |
| --split-manifest artifacts\homology-final\homology_split.json ` |
| --output-dir artifacts\training |
| ``` |
|
|
| (`artifacts/homology-final/homology_split.json` is included byte-identical inside |
| the release archive; the copy under `data/` here is the same file with its one |
| embedded local path redacted.) |
|
|
| ## 5. Reproduce the frozen baseline evaluation |
|
|
| The baseline checkpoint `artifacts/full-homology-baseline/best.pt` ships inside |
| the release archive. Evaluate the test partition: |
|
|
| ```powershell |
| python -m biocandidate.cli evaluate ` |
| --checkpoint artifacts\full-homology-baseline\best.pt ` |
| --data "<path>\Kcat_combination_0918_wildtype_mutant.json" ` |
| --manifest artifacts\unikp_audit.json ` |
| --split-manifest artifacts\homology-final\homology_split.json ` |
| --partition test ` |
| --output artifacts\full-homology-baseline\test_metrics.json |
| ``` |
|
|
| Reference result: `data/full-homology-baseline/test_metrics.json`. |
|
|
| > torch >= 2.6 note: `predict`/`evaluate` checkpoint loading with |
| > `weights_only=True` rejects pre-2.6 checkpoints. Install `torch<2.6` for CLI |
| > reproduction, or use the workbench server path documented in the README. |
| |
| ## 6. License obligations |
| |
| - The corpus rows stay out of public archives: upstream terms are unresolved |
| (`configs/data_license_inventory.json`, corpus `unikp-kcat-development-corpus`). |
| - If you redistribute anything derived from the corpus, resolve the upstream terms |
| first and cite the UniKP and DLKcat papers. |
| - EnzEngDB v1 (CC-BY-4.0) and the Lunzer IMDH landscape (CC0) have their own |
| attribution requirements documented in the dataset card. |
| |
