Configuration

Promotech

Promotech is an existing bacterial promoter predictor in the ProkBERT evaluation.

Sources

ProkBERT family: genomic language models for microbiome applications · 2 Materials and methods/2.3 Application I: bacterial promoter prediction/2.3.1 Dataset overview/2.3.1.2 Dataset construction for multispecies train, test and validation sets (paragraph 6); 3 Results and discussion/3.3 ProkBERT performs accurately and robustly in promoter sequence recognition (paragraph 11)

1 evaluation · 4 metric rows

How it worksEvaluated procedure (conceptual)

Conceptual input–method–output guide. Check the procedure text and linked evaluation for fitted components, additional inputs and exact settings.

Sources

ProkBERT family: genomic language models for microbiome applications · 2 Materials and methods (paragraph 1); 3 Results and discussion/3.3 ProkBERT performs accurately and robustly in promoter sequence recognition (paragraph 11)

At a glance

Model type

Random-forest promoter classifier; this record is the paper-specific evaluated configuration.

Sources

BioinformaticsLabAtMUN/Promotech README.md · README.md model description

Biological inputs

Bacterial DNA promoter windows

Sources

ProkBERT family: genomic language models for microbiome applications · 2 Materials and methods/2.3 Application I: bacterial promoter prediction/2.3.1 Dataset overview/2.3.1.2 Dataset construction for multispecies train, test and validation sets (paragraph 6); 2 Materials and methods/2.3 Application I: bacterial promoter prediction (paragraph 1)

Outputs

Promoter classifications

Sources

ProkBERT family: genomic language models for microbiome applications · 2 Materials and methods/2.3 Application I: bacterial promoter prediction/2.3.1 Dataset overview/2.3.1.2 Dataset construction for multispecies train, test and validation sets (paragraph 6); 2 Materials and methods/2.5 Applied metrics (paragraph 1)

limited source coverage · Automated source review, 2026-09-16. All specifications and missing details

Evaluations and results

Release 2026-09-17-d277315f7d76 · 1 evaluation · 4 metric rows. Different protocols are not a single leaderboard.

Evaluation setupMetricEvidence origin

Results grouped by the exact reported evaluation
Metric and finding	Coverage and uncertainty	Evidence
Promotech: E. coli sigma70 promoter prediction Configuration: PromotechProtocol: E. coli sigma70 independent promoter test (E. coli sigma70 promoter prediction)Dataset: E. coli sigma70 promoter dataset Test-only evaluation on Cassiano and Silva-Rocha 2020 data; methods have different training histories. 865 high-evidence RegulonDB 10.5 promoters and 1,000 nucleotide-distribution-matched negative sequences. Promoter exact matches removed from model training. Independent external evaluation · Evaluation metadata: needs review
0.71 Accuracy Unit: unitless · Direction: higher	Uncertainty: not reported in legacy extract Scored: Not reported · Eligible: Not reported	source checkedProkBERT family: genomic language models for microbiome applications; ProkBERT family: genomic language models for microbiome applications · Table 3, Promotech row, Accuracy column Source checking is not independent reproduction.
0.49 Sensitivity Unit: fraction · Direction: higher	Uncertainty: unreported Scored: Not reported · Eligible: Not reported	source checkedProkBERT family: genomic language models for microbiome applications · Table 3, row Promotech, column Sensitivity; XML row13 column4 Source checking is not independent reproduction.
0.43 MCC Unit: dimensionless · Direction: higher	Uncertainty: unreported Scored: Not reported · Eligible: Not reported	source checkedProkBERT family: genomic language models for microbiome applications · Table 3, row Promotech, column MCC; XML row13 column3 Source checking is not independent reproduction.
0.90 Specificity Unit: fraction · Direction: higher	Uncertainty: unreported Scored: Not reported · Eligible: Not reported	source checkedProkBERT family: genomic language models for microbiome applications · Table 3, row Promotech, column Specificity; XML row13 column5 Source checking is not independent reproduction.

How it works

How the evaluated method works

The official method uses a random forest on binary-encoded promoter sequences; the study evaluates it as a comparator, separate from ProkBERT training.

Sources

BioinformaticsLabAtMUN/Promotech README.md · README.md; introduction and model-installation instructions

Underlying method and version boundaries

Promotech’s selected model uses binary-encoded 40-bp promoter windows and a random forest. Its released workflow also scans genomes with a sliding window; the ProkBERT table does not pin the historical fitted model file.

Sources

BioinformaticsLabAtMUN/Promotech README.md · README.md; introduction, model description, pretrained-model and usage sections at pinned revision

What was evaluated

The linked evaluation record identifies Promotech: E. coli sigma70 promoter prediction. Its dataset, split, adaptation and evidence origin remain attached to the reported results.

Sources

ProkBERT family: genomic language models for microbiome applications · The named evaluation’s methods and comparison table; exact preserved evaluation IDs: evaluation-lit-034

Strengths and limitations

Strengths and considerations

Adds an established specialist baseline to the transformer comparison.
Sources
ProkBERT family: genomic language models for microbiome applications · 2 Materials and methods/2.4 Application II: phage sequence analysis/2.4.1 Phage dataset description (paragraph 5); 2 Materials and methods (paragraph 1)

Limitations and conditions

The ProkBERT comparison does not uniquely pin every implementation and fitted-model artifact; these cannot be filled from the comparator name alone.
Sources
ProkBERT family: genomic language models for microbiome applications · 1 Introduction (paragraph 8); 4 Conclusion (paragraph 6)

Profile review details

Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction.

Stable record: reported-model-0d147487bf97be

Specifications

Inputs, training, access and other details

Explanatory profile: limited source coverage · Automated source review, 2026-09-16. Review applies to the cited claims; unresolved fields are listed below. Numerical results retain their own review status.

Inputs, outputs and configuration
Property	Description and evidence
Model type	Random-forest promoter classifier; this record is the paper-specific evaluated configuration. Sources BioinformaticsLabAtMUN/Promotech README.md · README.md model description
Architecture / procedure	The official method uses a random forest on binary-encoded promoter sequences; the study evaluates it as a comparator, separate from ProkBERT training. Sources BioinformaticsLabAtMUN/Promotech README.md · README.md; introduction and model-installation instructions
Biological inputs	Bacterial DNA promoter windows Sources ProkBERT family: genomic language models for microbiome applications · 2 Materials and methods/2.3 Application I: bacterial promoter prediction/2.3.1 Dataset overview/2.3.1.2 Dataset construction for multispecies train, test and validation sets (paragraph 6); 2 Materials and methods/2.3 Application I: bacterial promoter prediction (paragraph 1)
Outputs	Promoter classifications Sources ProkBERT family: genomic language models for microbiome applications · 2 Materials and methods/2.3 Application I: bacterial promoter prediction/2.3.1 Dataset overview/2.3.1.2 Dataset construction for multispecies train, test and validation sets (paragraph 6); 2 Materials and methods/2.5 Applied metrics (paragraph 1)
Parameters	Not applicable to a neural parameter count: the selected predictor is a random forest. · Not applicable Sources BioinformaticsLabAtMUN/Promotech README.md · README.md; introduction and model-installation instructions
Known versions / configuration	Promotech is the comparison-table label; that label does not specify an immutable weight revision. · Not reported in inspected sources Sources ProkBERT family: genomic language models for microbiome applications · Model identification in the comparison table and corresponding Methods; immutable checkpoint revision is not supplied by the table label.
Training data / fitting	The original selected model is trained across nine bacterial species and validated on four held-out species. The ProkBERT comparison does not identify a new fit or immutable model-file digest. Sources BioinformaticsLabAtMUN/Promotech README.md · README.md; introduction and model-installation instructions
Context limits	The official predictor accepts 40-bp windows and scans whole bacterial genomes with a sliding window. Sources BioinformaticsLabAtMUN/Promotech README.md · README.md; introduction and model-installation instructions
Access	Official upstream implementation and usage documentation: https://github.com/BioinformaticsLabAtMUN/Promotech/blob/56251ad9b883ef831b4753fc623d5ec970fe65e0/README.md. This pinned documentation revision is not automatically the evaluated weight revision. Sources BioinformaticsLabAtMUN/Promotech README.md · README.md; installation, model download and usage instructions
Code licence	GNU GPL version 3 (upstream repository code at the cited revision; this does not establish every dependency or historical checkpoint licence). Sources BioinformaticsLabAtMUN/Promotech LICENSE · LICENSE; complete licence text
Weights licence	The inspected model-access documentation does not explicitly identify terms for this exact evaluated checkpoint or fitted head; repository code terms are shown separately. · Not reported in inspected sources Sources BioinformaticsLabAtMUN/Promotech README.md · README.md; checkpoint/access documentation and licence scope

Evidence table

Inspect claims, sources and review details

Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.

One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.

20 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-09-17-d277315f7d76
Property and statement	Original source and location	Review and provenance
Diagram caption Conceptual input–method–output guide. Check the procedure text and linked evaluation for fitted components, additional inputs and exact settings. Individual claims	ProkBERT family: genomic language models for microbiome applications Original source ↗ 2 Materials and methods (paragraph 1); 3 Results and discussion/3.3 ProkBERT performs accurately and robustly in promoter sequence recognition (paragraph 11) Version: PMC10810988.1 Retrieved: 2026-09-16T10:33:36.197Z	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.diagram.caption` Source artifact SHA-256: `8610e2a54aa877c8dc565a9cdb6e82099f284c5e0907a52cab18d994ea732436` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Diagram steps ["Bacterial DNA promoter windows","Promotech","Promoter classifications"] Individual claims	ProkBERT family: genomic language models for microbiome applications Original source ↗ 2 Materials and methods (paragraph 1); 3 Results and discussion/3.3 ProkBERT performs accurately and robustly in promoter sequence recognition (paragraph 11) Version: PMC10810988.1 Retrieved: 2026-09-16T10:33:36.197Z	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.diagram.steps` Source artifact SHA-256: `8610e2a54aa877c8dc565a9cdb6e82099f284c5e0907a52cab18d994ea732436` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Diagram title Evaluated procedure (conceptual) Individual claims	ProkBERT family: genomic language models for microbiome applications Original source ↗ 2 Materials and methods (paragraph 1); 3 Results and discussion/3.3 ProkBERT performs accurately and robustly in promoter sequence recognition (paragraph 11) Version: PMC10810988.1 Retrieved: 2026-09-16T10:33:36.197Z	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.diagram.title` Source artifact SHA-256: `8610e2a54aa877c8dc565a9cdb6e82099f284c5e0907a52cab18d994ea732436` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Model type Random-forest promoter classifier; this record is the paper-specific evaluated configuration. Individual claims	BioinformaticsLabAtMUN/Promotech README.md Original source ↗ README.md model description Version: 56251ad9b883ef831b4753fc623d5ec970fe65e0 Retrieved: 2026-09-16T20:40:28.842295+00:00	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.0.value` Source artifact SHA-256: `51050c0bf5982be985dd87e450ea5c2408a2d87cd32c679fc639246d64e5ca80` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Architecture / procedure The official method uses a random forest on binary-encoded promoter sequences; the study evaluates it as a comparator, separate from ProkBERT training. Individual claims	BioinformaticsLabAtMUN/Promotech README.md Original source ↗ README.md; introduction and model-installation instructions Version: 56251ad9b883ef831b4753fc623d5ec970fe65e0 Retrieved: 2026-09-16T20:40:28.842295+00:00	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.1.value` Source artifact SHA-256: `51050c0bf5982be985dd87e450ea5c2408a2d87cd32c679fc639246d64e5ca80` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Weights licence The inspected model-access documentation does not explicitly identify terms for this exact evaluated checkpoint or fitted head; repository code terms are shown separately. Individual claims	BioinformaticsLabAtMUN/Promotech README.md Original source ↗ README.md; checkpoint/access documentation and licence scope Version: 56251ad9b883ef831b4753fc623d5ec970fe65e0 Retrieved: 2026-09-16T20:40:28.842295+00:00	unreported automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.10.value` Source artifact SHA-256: `51050c0bf5982be985dd87e450ea5c2408a2d87cd32c679fc639246d64e5ca80` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Biological inputs Bacterial DNA promoter windows Individual claims	ProkBERT family: genomic language models for microbiome applications Original source ↗ 2 Materials and methods/2.3 Application I: bacterial promoter prediction/2.3.1 Dataset overview/2.3.1.2 Dataset construction for multispecies train, test and validation sets (paragraph 6); 2 Materials and methods/2.3 Application I: bacterial promoter prediction (paragraph 1) Version: PMC10810988.1 Retrieved: 2026-09-16T10:33:36.197Z	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.2.value` Source artifact SHA-256: `8610e2a54aa877c8dc565a9cdb6e82099f284c5e0907a52cab18d994ea732436` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Outputs Promoter classifications Individual claims	ProkBERT family: genomic language models for microbiome applications Original source ↗ 2 Materials and methods/2.3 Application I: bacterial promoter prediction/2.3.1 Dataset overview/2.3.1.2 Dataset construction for multispecies train, test and validation sets (paragraph 6); 2 Materials and methods/2.5 Applied metrics (paragraph 1) Version: PMC10810988.1 Retrieved: 2026-09-16T10:33:36.197Z	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.3.value` Source artifact SHA-256: `8610e2a54aa877c8dc565a9cdb6e82099f284c5e0907a52cab18d994ea732436` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Parameters Not applicable to a neural parameter count: the selected predictor is a random forest. Individual claims	BioinformaticsLabAtMUN/Promotech README.md Original source ↗ README.md; introduction and model-installation instructions Version: 56251ad9b883ef831b4753fc623d5ec970fe65e0 Retrieved: 2026-09-16T20:40:28.842295+00:00	inapplicable automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.4.value` Source artifact SHA-256: `51050c0bf5982be985dd87e450ea5c2408a2d87cd32c679fc639246d64e5ca80` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Known versions / configuration Promotech is the comparison-table label; that label does not specify an immutable weight revision. Individual claims	ProkBERT family: genomic language models for microbiome applications Original source ↗ Model identification in the comparison table and corresponding Methods; immutable checkpoint revision is not supplied by the table label. Version: PMC10810988.1 Retrieved: 2026-09-16T10:33:36.197Z	unreported automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.5.value` Source artifact SHA-256: `8610e2a54aa877c8dc565a9cdb6e82099f284c5e0907a52cab18d994ea732436` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact

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Sources and history

Release 2026-09-17-d277315f7d76 · Record review: needs review

3 source records and release history

ProkBERT family: genomic language models for microbiome applications · Original source · PMC10810988.1
BioinformaticsLabAtMUN/Promotech README.md · Original source · 56251ad9b883ef831b4753fc623d5ec970fe65e0
BioinformaticsLabAtMUN/Promotech LICENSE · Original source · 56251ad9b883ef831b4753fc623d5ec970fe65e0

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Technical metadata and extraction receipts

Stable ID: reported-model-0d147487bf97be

areas: microbes-communities
entity level: method
version: Not reported
reported name: Promotech
historical missing metadata: version: not_reported_in_legacy_extract; checkpoint revision: not_reported_in_legacy_extract; training data: not_reported_in_legacy_extract; licence: not_reported_in_legacy_extract
metadata review scope: historical_missing_metadata preserves the original discovery state. Current descriptive evidence and missingness are recorded in profile.facts; numerical-result review is separate.
legacy kinds: model
entity classification: review date: 2026-09-17; rationale: This source-scoped entry preserves the method/configuration actually named in an evaluation. It is neither a global family identity nor proof of an immutable checkpoint; the linked evaluation retains adaptation, fitting and scoring details.; source ids: evidence-reported-base-promotech-readme-md; prokbert-2024; source locator: README.md; introduction and model-installation instructions | README.md model description | 2 Materials and methods/2.3 Application I: bacterial promoter prediction/2.3.1 Dataset overview/2.3.1.2 Dataset construction for multispecies train, test and validation sets (paragraph 6); 3 Results and discussion/3.3 ProkBERT performs accurately and robustly in promoter sequence recognition (paragraph 11); ambiguities: Configuration means the source-labelled evaluated identity. It does not establish missing checkpoint hashes, default settings or equivalence to same-named records in other papers.

Related records

model: Promotech: E. coli sigma70 promoter prediction

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