Model type
Study-specific predictive method; this record is the paper-specific evaluated configuration.
Configuration
iPro-MP
iPro-MP is a transformer-based prokaryotic promoter classifier evaluated across 23 species.
Sources
iPro-MP: a BERT-based model to predict multiple prokaryotic promoters · Discussion (paragraph 1); Results/iPro-MP outperforms classical and deep learning baselines across species (paragraph 4)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
iPro-MP: a BERT-based model to predict multiple prokaryotic promoters · Discussion (paragraph 1); Methods/DNABERT model (paragraph 3)At a glance
Biological inputs
81-bp DNA windows from −60 to +20 relative to the transcription start site
Sources
iPro-MP: a BERT-based model to predict multiple prokaryotic promoters · Background (paragraph 1); Results/iPro-MP exhibits excellent performance and robustness in multi-species promoter prediction (paragraph 4)Outputs
Promoter versus non-promoter classification
Sources
iPro-MP: a BERT-based model to predict multiple prokaryotic promoters · Results/iPro-MP outperforms classical and deep learning baselines across species (paragraph 1); Results/iPro-MP outperforms existing tools in multi-species promoter prediction (paragraph 3)limited source coverage · Automated source review, 2026-09-16. All specifications and missing details
Evaluations and results
Release 2026-09-17-d277315f7d76 · 1 evaluation · 1 metric row. Different protocols are not a single leaderboard.
| Metric and finding | Coverage and uncertainty | Evidence |
|---|---|---|
| iPro-MP: Multi-species prokaryotic promoter detection Configuration: iPro-MPTask: Multi-species prokaryotic promoter detectionDataset: 23 independent prokaryotic promoter test sets Average over independent testing sets. Author-reported evaluation · Evaluation metadata: needs review | ||
| 0.935 Mean AUC Unit: unitless · Direction: unknown | Uncertainty: not reported in legacy extract Scored: Not reported · Eligible: Not reported | source checkediPro-MP: a BERT-based model to predict multiple prokaryotic promoters · Table 2, iPro-MP row, AUC column Source checking is not independent reproduction. |
How it works
How the evaluated method works
Multi-head attention models DNA-sequence patterns in a species-specific promoter-prediction framework.
Sources
iPro-MP: a BERT-based model to predict multiple prokaryotic promoters · Discussion (paragraph 1); Methods/DNABERT model (paragraph 3)What was evaluated
The linked evaluation record identifies iPro-MP: Multi-species prokaryotic promoter detection. Its dataset, split, adaptation and evidence origin remain attached to the reported results.
Sources
iPro-MP: a BERT-based model to predict multiple prokaryotic promoters · The named evaluation’s methods and comparison table; exact preserved evaluation IDs: evaluation-lit-b3-033Strengths and limitations
Strengths and considerations
- Includes model and non-model prokaryotic species with explicit cross-species tests.
Sources
iPro-MP: a BERT-based model to predict multiple prokaryotic promoters · Results/iPro-MP reveals the species-specificity at the sequential level (paragraph 1); Results/iPro-MP outperforms classical and deep learning baselines across species (paragraph 1)
Limitations and conditions
- Cross-species experiments motivate species-specific models; a strong within-species result is not evidence of universal promoter recognition.
Sources
iPro-MP: a BERT-based model to predict multiple prokaryotic promoters · Results/iPro-MP reveals the species-specificity at the sequential level (paragraph 5); Results/iPro-MP reveals the species-specificity at the sequential level (paragraph 1)
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-9a200c55b0e03eSpecifications
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.
| Property | Description and evidence |
|---|---|
| Model type | Study-specific predictive method; this record is the paper-specific evaluated configuration.SourcesiPro-MP: a BERT-based model to predict multiple prokaryotic promoters · Discussion (paragraph 1); Methods/DNABERT model (paragraph 3) |
| Architecture / procedure | Multi-head attention models DNA-sequence patterns in a species-specific promoter-prediction framework.SourcesiPro-MP: a BERT-based model to predict multiple prokaryotic promoters · Discussion (paragraph 1); Methods/DNABERT model (paragraph 3) |
| Biological inputs | 81-bp DNA windows from −60 to +20 relative to the transcription start siteSourcesiPro-MP: a BERT-based model to predict multiple prokaryotic promoters · Background (paragraph 1); Results/iPro-MP exhibits excellent performance and robustness in multi-species promoter prediction (paragraph 4) |
| Outputs | Promoter versus non-promoter classificationSourcesiPro-MP: a BERT-based model to predict multiple prokaryotic promoters · Results/iPro-MP outperforms classical and deep learning baselines across species (paragraph 1); Results/iPro-MP outperforms existing tools in multi-species promoter prediction (paragraph 3) |
| Parameters | An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. · Not reported in inspected sourcesSources (2)iPro-MP: a BERT-based model to predict multiple prokaryotic promoters; Jackie-Suv/iPro-MP README.md · Methods; Methods/Data collection and preprocessing; Methods/DNABERT model; Methods/Fine-tuning of DNABERT model; Methods/Performance evaluation; inspected for aggregate parameter count (component sizes are not added without an exact configuration); README.md at pinned repository revision |
| Known versions / configuration | iPro-MP is the comparison-table label; that label does not specify an immutable weight revision. · Not reported in inspected sourcesSourcesiPro-MP: a BERT-based model to predict multiple prokaryotic promoters · Model identification in the comparison table and corresponding Methods; immutable checkpoint revision is not supplied by the table label. |
| Training data / fitting | 107,286 promoter sequences from the Prokaryotic Promoter Database, filtered at 0.8 sequence identity; species selection generally requires more than 1,000 validated promoters.SourcesiPro-MP: a BERT-based model to predict multiple prokaryotic promoters · Methods/Data collection and preprocessing (paragraph 1); Results/iPro-MP reveals the species-specificity at the sequential level (paragraph 5) |
| Context limits | 81 nucleotides per example.SourcesiPro-MP: a BERT-based model to predict multiple prokaryotic promoters · Results/iPro-MP outperforms classical and deep learning baselines across species (paragraph 3); Methods/DNABERT model (paragraph 4) |
| Access | Official study implementation and usage documentation: https://github.com/Jackie-Suv/iPro-MP/blob/4266b521bc6617db939c5871cb1b6850dff63fdb/README.md. This pinned documentation revision is not automatically the evaluated weight revision.SourcesJackie-Suv/iPro-MP README.md · README.md; installation, model download and usage instructions |
| Code licence | No explicit code licence was established from the paper’s availability statement and inspected repository-root documentation. · Not reported in inspected sourcesSourcesJackie-Suv/iPro-MP README.md · README.md and repository-root licence-file search |
| 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 sourcesSourcesJackie-Suv/iPro-MP 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
| 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 | iPro-MP: a BERT-based model to predict multiple prokaryotic promoters Discussion (paragraph 1); Methods/DNABERT model (paragraph 3) Version: version of record | source checked automated source review · 2026-09-16 Audit detailsPrimary 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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram steps ["81-bp DNA windows from −60 to +20 relative to the transcription start site","iPro-MP","Promoter versus non-promoter classification"] Individual claims | iPro-MP: a BERT-based model to predict multiple prokaryotic promoters Discussion (paragraph 1); Methods/DNABERT model (paragraph 3) Version: version of record | source checked automated source review · 2026-09-16 Audit detailsPrimary 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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram title Evaluated procedure (conceptual) Individual claims | iPro-MP: a BERT-based model to predict multiple prokaryotic promoters Discussion (paragraph 1); Methods/DNABERT model (paragraph 3) Version: version of record | source checked automated source review · 2026-09-16 Audit detailsPrimary 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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Model type Study-specific predictive method; this record is the paper-specific evaluated configuration. Individual claims | iPro-MP: a BERT-based model to predict multiple prokaryotic promoters Discussion (paragraph 1); Methods/DNABERT model (paragraph 3) Version: version of record | source checked automated source review · 2026-09-16 Audit detailsPrimary 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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Architecture / procedure Multi-head attention models DNA-sequence patterns in a species-specific promoter-prediction framework. Individual claims | iPro-MP: a BERT-based model to predict multiple prokaryotic promoters Discussion (paragraph 1); Methods/DNABERT model (paragraph 3) Version: version of record | source checked automated source review · 2026-09-16 Audit detailsPrimary 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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| 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 | Jackie-Suv/iPro-MP README.md README.md; checkpoint/access documentation and licence scope Version: 4266b521bc6617db939c5871cb1b6850dff63fdb | unreported automated source review · 2026-09-16 Audit detailsPrimary 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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Biological inputs 81-bp DNA windows from −60 to +20 relative to the transcription start site Individual claims | iPro-MP: a BERT-based model to predict multiple prokaryotic promoters Background (paragraph 1); Results/iPro-MP exhibits excellent performance and robustness in multi-species promoter prediction (paragraph 4) Version: version of record | source checked automated source review · 2026-09-16 Audit detailsPrimary 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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Outputs Promoter versus non-promoter classification Individual claims | iPro-MP: a BERT-based model to predict multiple prokaryotic promoters Results/iPro-MP outperforms classical and deep learning baselines across species (paragraph 1); Results/iPro-MP outperforms existing tools in multi-species promoter prediction (paragraph 3) Version: version of record | source checked automated source review · 2026-09-16 Audit detailsPrimary 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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Parameters An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. Individual claims | Jackie-Suv/iPro-MP README.md Methods; Methods/Data collection and preprocessing; Methods/DNABERT model; Methods/Fine-tuning of DNABERT model; Methods/Performance evaluation; inspected for aggregate parameter count (component sizes are not added without an exact configuration); README.md at pinned repository revision Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 4266b521bc6617db939c5871cb1b6850dff63fdb | unreported automated source review · 2026-09-16 Audit detailsPrimary 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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Parameters An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. Individual claims | iPro-MP: a BERT-based model to predict multiple prokaryotic promoters Methods; Methods/Data collection and preprocessing; Methods/DNABERT model; Methods/Fine-tuning of DNABERT model; Methods/Performance evaluation; inspected for aggregate parameter count (component sizes are not added without an exact configuration); README.md at pinned repository revision Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: version of record | unreported automated source review · 2026-09-16 Audit detailsPrimary 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: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Sources and history
Release 2026-09-17-d277315f7d76 · Record review: needs review
2 source records and release history
- iPro-MP: a BERT-based model to predict multiple prokaryotic promoters · Original source · version of record
- Jackie-Suv/iPro-MP README.md · Original source · 4266b521bc6617db939c5871cb1b6850dff63fdb
Technical metadata and extraction receipts
Stable ID: reported-model-9a200c55b0e03e
- areas
- microbes-communities
- entity level
- method
- version
- Not reported
- reported name
- iPro-MP
- 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: ipromp-2025; source locator: Discussion (paragraph 1); Methods/DNABERT model (paragraph 3) | Discussion (paragraph 1); Results/iPro-MP outperforms classical and deep learning baselines across species (paragraph 4); 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.