Model type
Hybrid convolutional/transformer pipeline; this record is the paper-specific evaluated configuration.
Configuration
BPfold
BPfold predicts RNA secondary structure by combining learned sequence features with base-pair motif energies.
Sources
Deep generalizable prediction of RNA secondary structure via base pair motif energy · Discussion (paragraph 5); Abstract (paragraph 2)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
Deep generalizable prediction of RNA secondary structure via base pair motif energy · Methods/Deep neural network with base pair attention (paragraph 1); Methods/Deep neural network with base pair attention (paragraph 4)At a glance
Biological inputs
RNA sequences and a precomputed base-pair motif-energy library
Sources
Deep generalizable prediction of RNA secondary structure via base pair motif energy · Methods/Base pair motif energy as thermodynamic prior (paragraph 4); Abstract (paragraph 2)Outputs
RNA secondary-structure base-pair predictions
Sources
Deep generalizable prediction of RNA secondary structure via base pair motif energy · Discussion (paragraph 5); Abstract (paragraph 2)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.
| Metric and finding | Coverage and uncertainty | Evidence |
|---|---|---|
| BPfold: RNA secondary structure Family-wise RNA secondary-structure evaluation; macro-average canonical base-pair metrics. Author-reported evaluation · Evaluation metadata: needs review | ||
| 0.814 F1 Unit: unitless · Direction: higher | Uncertainty: not reported in legacy extract Scored: Not reported · Eligible: Not reported | source checkedDeep generalizable prediction of RNA secondary structure via base pair motif energy · Table 2, BPfold row, PDB F1 column Source checking is not independent reproduction. |
| 0.801 Recall Unit: unitless · Direction: higher | Uncertainty: unreported Scored: Not reported · Eligible: Not reported | source checkedDeep generalizable prediction of RNA secondary structure via base pair motif energy · Table 2 (Tab2), row 3 BPfold, column 9: PDB Recall Source checking is not independent reproduction. |
| 0.840 Precision Unit: unitless · Direction: higher | Uncertainty: unreported Scored: Not reported · Eligible: Not reported | source checkedDeep generalizable prediction of RNA secondary structure via base pair motif energy · Table 2 (Tab2), row 3 BPfold, column 8: PDB Precision Source checking is not independent reproduction. |
| 0.817 INF Unit: unitless · Direction: higher | Uncertainty: unreported Scored: Not reported · Eligible: Not reported | source checkedDeep generalizable prediction of RNA secondary structure via base pair motif energy · Table 2 (Tab2), row 3 BPfold, column 6: PDB INF Source checking is not independent reproduction. |
How it works
How the evaluated method works
Modified transformer blocks combine sequence attention with a hybrid convolutional branch operating on motif-energy maps. Squeeze-and-excitation recalibrates channels, while pair attention integrates thermodynamic priors into base-pair prediction.
Sources
Deep generalizable prediction of RNA secondary structure via base pair motif energy · Methods/Deep neural network with base pair attention (paragraph 1); Methods/Deep neural network with base pair attention (paragraph 4)What was evaluated
The linked evaluation record identifies BPfold: RNA secondary structure. Its dataset, split, adaptation and evidence origin remain attached to the reported results.
Sources
Deep generalizable prediction of RNA secondary structure via base pair motif energy · The named evaluation’s methods and comparison table; exact preserved evaluation IDs: evaluation-lit-011Strengths and limitations
Strengths and considerations
- Family-wise evaluation explicitly examines transfer to RNA families not represented in training.
Sources
Deep generalizable prediction of RNA secondary structure via base pair motif energy · Results/Evaluating BPfold on family-wise datasets (paragraph 1); Results/Evaluating BPfold on sequence-wise datasets (paragraph 1)
Limitations and conditions
- The thermodynamic motif library is a prior, not a guarantee of generalisation to every RNA family or in-vivo folding condition.
Sources
Deep generalizable prediction of RNA secondary structure via base pair motif energy · Abstract (paragraph 2); Discussion (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-c464bface507eeSpecifications
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 | Hybrid convolutional/transformer pipeline; this record is the paper-specific evaluated configuration.SourcesDeep generalizable prediction of RNA secondary structure via base pair motif energy · Methods/Deep neural network with base pair attention (paragraph 1); Methods/Deep neural network with base pair attention (paragraph 4) |
| Architecture / procedure | Modified transformer blocks combine sequence attention with a hybrid convolutional branch operating on motif-energy maps. Squeeze-and-excitation recalibrates channels, while pair attention integrates thermodynamic priors into base-pair prediction.SourcesDeep generalizable prediction of RNA secondary structure via base pair motif energy · Methods/Deep neural network with base pair attention (paragraph 1); Methods/Deep neural network with base pair attention (paragraph 4) |
| Biological inputs | RNA sequences and a precomputed base-pair motif-energy librarySourcesDeep generalizable prediction of RNA secondary structure via base pair motif energy · Methods/Base pair motif energy as thermodynamic prior (paragraph 4); Abstract (paragraph 2) |
| Outputs | RNA secondary-structure base-pair predictionsSourcesDeep generalizable prediction of RNA secondary structure via base pair motif energy · Discussion (paragraph 5); Abstract (paragraph 2) |
| Parameters | 7,962,416 parameters in the published BPfold configuration.SourcesBPfold supplementary information · Supplementary Table 6, BPfold row |
| Known versions / configuration | BPfold is the comparison-table label; that label does not specify an immutable weight revision. · Not reported in inspected sourcesSourcesDeep generalizable prediction of RNA secondary structure via base pair motif energy · Model identification in the comparison table and corresponding Methods; immutable checkpoint revision is not supplied by the table label. |
| Training data / fitting | Sequence-wise and family-wise RNA structure datasets described in the paper; the motif library enumerates local base-pair neighbourhoods.SourcesDeep generalizable prediction of RNA secondary structure via base pair motif energy · Results/Assessing the effectiveness of base pair motif energy (paragraph 1); Results/Evaluating BPfold on sequence-wise datasets (paragraph 3) |
| Context limits | BPfold is trained on RNAs of at most 600 nucleotides from RNAStrAlign and bpRNA; family-wise tests use separate curated sets.SourcesDeep generalizable prediction of RNA secondary structure via base pair motif energy · Table Tab2 (paragraph 1); Table Tab1 (paragraph 1) |
| Access | Official study implementation and usage documentation: https://github.com/heqin-zhu/BPfold/blob/d37d6aa10cbca13e590ff83917fc4d63fec2ddbc/README.md. This pinned documentation revision is not automatically the evaluated weight revision.Sourcesheqin-zhu/BPfold README.md · README.md; installation, model download and usage instructions |
| Code licence | MIT (study repository code at the cited revision; this does not establish every dependency or historical checkpoint licence).Sourcesheqin-zhu/BPfold 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 sourcesSourcesheqin-zhu/BPfold 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.
19 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 | Deep generalizable prediction of RNA secondary structure via base pair motif energy Methods/Deep neural network with base pair attention (paragraph 1); Methods/Deep neural network with base pair attention (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 |
| Diagram steps ["RNA sequences and a precomputed base-pair motif-energy library","BPfold","RNA secondary-structure base-pair predictions"] Individual claims | Deep generalizable prediction of RNA secondary structure via base pair motif energy Methods/Deep neural network with base pair attention (paragraph 1); Methods/Deep neural network with base pair attention (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 |
| Diagram title Evaluated procedure (conceptual) Individual claims | Deep generalizable prediction of RNA secondary structure via base pair motif energy Methods/Deep neural network with base pair attention (paragraph 1); Methods/Deep neural network with base pair attention (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 |
| Model type Hybrid convolutional/transformer pipeline; this record is the paper-specific evaluated configuration. Individual claims | Deep generalizable prediction of RNA secondary structure via base pair motif energy Methods/Deep neural network with base pair attention (paragraph 1); Methods/Deep neural network with base pair attention (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 |
| Architecture / procedure Modified transformer blocks combine sequence attention with a hybrid convolutional branch operating on motif-energy maps. Squeeze-and-excitation recalibrates channels, while pair attention integrates thermodynamic priors into base-pair prediction. Individual claims | Deep generalizable prediction of RNA secondary structure via base pair motif energy Methods/Deep neural network with base pair attention (paragraph 1); Methods/Deep neural network with base pair attention (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 |
| 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 | heqin-zhu/BPfold README.md README.md; checkpoint/access documentation and licence scope Version: d37d6aa10cbca13e590ff83917fc4d63fec2ddbc | 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 RNA sequences and a precomputed base-pair motif-energy library Individual claims | Deep generalizable prediction of RNA secondary structure via base pair motif energy Methods/Base pair motif energy as thermodynamic prior (paragraph 4); Abstract (paragraph 2) 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 RNA secondary-structure base-pair predictions Individual claims | Deep generalizable prediction of RNA secondary structure via base pair motif energy Discussion (paragraph 5); Abstract (paragraph 2) 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 7,962,416 parameters in the published BPfold configuration. Individual claims | BPfold supplementary information Supplementary Table 6, BPfold row Version: s41467-025-60048-1 published supplement | 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 Archive member: 41467_2025_60048_MOESM1_ESM.pdf |
| Known versions / configuration BPfold is the comparison-table label; that label does not specify an immutable weight revision. Individual claims | Deep generalizable prediction of RNA secondary structure via base pair motif energy Model identification in the comparison table and corresponding Methods; immutable checkpoint revision is not supplied by the table label. 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
4 source records and release history
- Deep generalizable prediction of RNA secondary structure via base pair motif energy · Original source · version of record
- BPfold supplementary information · Original source · s41467-025-60048-1 published supplement
- heqin-zhu/BPfold README.md · Original source · d37d6aa10cbca13e590ff83917fc4d63fec2ddbc
- heqin-zhu/BPfold LICENSE · Original source · d37d6aa10cbca13e590ff83917fc4d63fec2ddbc
Technical metadata and extraction receipts
Stable ID: reported-model-c464bface507ee
- areas
- rna-transcriptomes
- entity level
- method
- version
- Not reported
- reported name
- BPfold
- 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: bpfold-2025; source locator: Methods/Deep neural network with base pair attention (paragraph 1); Methods/Deep neural network with base pair attention (paragraph 4) | Discussion (paragraph 5); Abstract (paragraph 2); 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.