Model type
Graph-based predictive method; this record is the paper-specific evaluated configuration.
Configuration
RLsite
RLsite combines pretrained RNA representations with structural graphs to identify small-molecule-binding sites.
Sources
RNA language model and graph attention network for RNA and small molecule binding sites prediction · 2 Materials and methods/2.4 Graph attention network/2.4.2 Feature aggregation and update (paragraph 2); 1 Introduction (paragraph 7)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
RNA language model and graph attention network for RNA and small molecule binding sites prediction · 4 Conclusions/4.1 Hybrid architecture leveraging complementary modalities (paragraph 1); 2 Materials and methods/2.2 Model architecture overview (paragraph 1)At a glance
Biological inputs
RNA sequence and graph-based RNA structural information
Sources
RNA language model and graph attention network for RNA and small molecule binding sites prediction · 1 Introduction (paragraph 7); 3 Results and discussions/3.3 Complementarity of graph attention networks and RNA language models (paragraph 2)Outputs
Small-molecule-binding nucleotide predictions
Sources
RNA language model and graph attention network for RNA and small molecule binding sites prediction · 2 Materials and methods/2.4 Graph attention network/2.4.2 Feature aggregation and update (paragraph 2); 3 Results and discussions/3.4 Consistent high performance of RLsite on the latest dataset T10 (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 |
|---|---|---|
| RLsite: RNA-small-molecule binding-site prediction RNA language-model plus graph-attention classifier Author-reported evaluation · Evaluation metadata: needs review | ||
| 0.828 AUC Unit: fraction · Direction: unknown | Uncertainty: not reported in legacy extract Scored: Not reported · Eligible: Not reported | source checkedRNA language model and graph attention network for RNA and small molecule binding sites prediction · Table 1, RLsite row, T18 AUC column Source checking is not independent reproduction. |
How it works
How the evaluated method works
RNA-language-model sequence features and graph attention capture nucleotide context and spatial/topological relationships for binding-site prediction.
Sources
RNA language model and graph attention network for RNA and small molecule binding sites prediction · 4 Conclusions/4.1 Hybrid architecture leveraging complementary modalities (paragraph 1); 2 Materials and methods/2.2 Model architecture overview (paragraph 1)What was evaluated
The linked evaluation record identifies RLsite: RNA-small-molecule binding-site prediction. Its dataset, split, adaptation and evidence origin remain attached to the reported results.
Sources
RNA language model and graph attention network for RNA and small molecule binding sites prediction · The named evaluation’s methods and comparison table; exact preserved evaluation IDs: evaluation-b2-rlsite-rna-binding-2025Strengths and limitations
Strengths and considerations
- Combines sequence and structural evidence and evaluates an independent public test set.
Sources
RNA language model and graph attention network for RNA and small molecule binding sites prediction · 2 Materials and methods/2.1 Benchmark datasets (paragraph 1); 2 Materials and methods/2.4 Graph attention network/2.4.3 Multi-head attention for improved representation (paragraph 1)
Limitations and conditions
- The training filters restrict sequence lengths and binding-site density; sequence-only methods do not receive equivalent inputs.
Sources
RNA language model and graph attention network for RNA and small molecule binding sites prediction · 3 Results and discussions/3.3 Complementarity of graph attention networks and RNA language models (paragraph 2); 3 Results and discussions/3.2 Secondary structure emerges as the dominant feature for RNA binding site prediction (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-52b9c685d99290Specifications
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 | Graph-based predictive method; this record is the paper-specific evaluated configuration.SourcesRNA language model and graph attention network for RNA and small molecule binding sites prediction · 4 Conclusions/4.1 Hybrid architecture leveraging complementary modalities (paragraph 1); 2 Materials and methods/2.2 Model architecture overview (paragraph 1) |
| Architecture / procedure | RNA-language-model sequence features and graph attention capture nucleotide context and spatial/topological relationships for binding-site prediction.SourcesRNA language model and graph attention network for RNA and small molecule binding sites prediction · 4 Conclusions/4.1 Hybrid architecture leveraging complementary modalities (paragraph 1); 2 Materials and methods/2.2 Model architecture overview (paragraph 1) |
| Biological inputs | RNA sequence and graph-based RNA structural informationSourcesRNA language model and graph attention network for RNA and small molecule binding sites prediction · 1 Introduction (paragraph 7); 3 Results and discussions/3.3 Complementarity of graph attention networks and RNA language models (paragraph 2) |
| Outputs | Small-molecule-binding nucleotide predictionsSourcesRNA language model and graph attention network for RNA and small molecule binding sites prediction · 2 Materials and methods/2.4 Graph attention network/2.4.2 Feature aggregation and update (paragraph 2); 3 Results and discussions/3.4 Consistent high performance of RLsite on the latest dataset T10 (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)RNA language model and graph attention network for RNA and small molecule binding sites prediction; SaisaiSun/RLsite README.md · 2 Materials and methods/2.1 Benchmark datasets; 2 Materials and methods/2.2 Model architecture overview; 2 Materials and methods/2.3 Pre-trained RNA language model; 2 Materials and methods/2.4 Graph attention network; 2 Materials and methods/2.4 Graph attention network/2.4.1 Graph attention mechanism; 2 Materials and methods/2.4 Graph attention network/2.4.2 Feature aggregation and update; 2 Materials and methods/2.4 Graph attention network/2.4.3 Multi-head attention for improved representation; 2 Materials and methods/2.5 Graph node representations; inspected for aggregate parameter count (component sizes are not added without an exact configuration); README.md at pinned repository revision |
| Known versions / configuration | RLsite is the comparison-table label; that label does not specify an immutable weight revision. · Not reported in inspected sourcesSourcesRNA language model and graph attention network for RNA and small molecule binding sites prediction · Model identification in the comparison table and corresponding Methods; immutable checkpoint revision is not supplied by the table label. |
| Training data / fitting | A merged RNAglib/RNAsite training collection; RNAglib filtering excludes chains above 440 nt and those with fewer than four binding sites.SourcesRNA language model and graph attention network for RNA and small molecule binding sites prediction · 2 Materials and methods/2.1 Benchmark datasets (paragraph 1); 3 Results and discussions/3.4 Consistent high performance of RLsite on the latest dataset T10 (paragraph 2) |
| Context limits | RNA chains longer than 440 nucleotides are excluded from the curated benchmark.SourcesRNA language model and graph attention network for RNA and small molecule binding sites prediction · 2 Materials and methods/2.1 Benchmark datasets (paragraph 1); 2 Materials and methods/2.1 Benchmark datasets (paragraph 2) |
| Access | Official study implementation and usage documentation: https://github.com/SaisaiSun/RLsite/blob/3d4a294aab295cbc1afd56b9ea6ced96e0717304/README.md. This pinned documentation revision is not automatically the evaluated weight revision.SourcesSaisaiSun/RLsite 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 sourcesSourcesSaisaiSun/RLsite 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 sourcesSourcesSaisaiSun/RLsite 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 | RNA language model and graph attention network for RNA and small molecule binding sites prediction 4 Conclusions/4.1 Hybrid architecture leveraging complementary modalities (paragraph 1); 2 Materials and methods/2.2 Model architecture overview (paragraph 1) Version: journal full text in PMC | 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 sequence and graph-based RNA structural information","RLsite","Small-molecule-binding nucleotide predictions"] Individual claims | RNA language model and graph attention network for RNA and small molecule binding sites prediction 4 Conclusions/4.1 Hybrid architecture leveraging complementary modalities (paragraph 1); 2 Materials and methods/2.2 Model architecture overview (paragraph 1) Version: journal full text in PMC | 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 | RNA language model and graph attention network for RNA and small molecule binding sites prediction 4 Conclusions/4.1 Hybrid architecture leveraging complementary modalities (paragraph 1); 2 Materials and methods/2.2 Model architecture overview (paragraph 1) Version: journal full text in PMC | 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 Graph-based predictive method; this record is the paper-specific evaluated configuration. Individual claims | RNA language model and graph attention network for RNA and small molecule binding sites prediction 4 Conclusions/4.1 Hybrid architecture leveraging complementary modalities (paragraph 1); 2 Materials and methods/2.2 Model architecture overview (paragraph 1) Version: journal full text in PMC | 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 RNA-language-model sequence features and graph attention capture nucleotide context and spatial/topological relationships for binding-site prediction. Individual claims | RNA language model and graph attention network for RNA and small molecule binding sites prediction 4 Conclusions/4.1 Hybrid architecture leveraging complementary modalities (paragraph 1); 2 Materials and methods/2.2 Model architecture overview (paragraph 1) Version: journal full text in PMC | 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 | SaisaiSun/RLsite README.md README.md; checkpoint/access documentation and licence scope Version: 3d4a294aab295cbc1afd56b9ea6ced96e0717304 | 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 sequence and graph-based RNA structural information Individual claims | RNA language model and graph attention network for RNA and small molecule binding sites prediction 1 Introduction (paragraph 7); 3 Results and discussions/3.3 Complementarity of graph attention networks and RNA language models (paragraph 2) Version: journal full text in PMC | 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 Small-molecule-binding nucleotide predictions Individual claims | RNA language model and graph attention network for RNA and small molecule binding sites prediction 2 Materials and methods/2.4 Graph attention network/2.4.2 Feature aggregation and update (paragraph 2); 3 Results and discussions/3.4 Consistent high performance of RLsite on the latest dataset T10 (paragraph 3) Version: journal full text in PMC | 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 | SaisaiSun/RLsite README.md 2 Materials and methods/2.1 Benchmark datasets; 2 Materials and methods/2.2 Model architecture overview; 2 Materials and methods/2.3 Pre-trained RNA language model; 2 Materials and methods/2.4 Graph attention network; 2 Materials and methods/2.4 Graph attention network/2.4.1 Graph attention mechanism; 2 Materials and methods/2.4 Graph attention network/2.4.2 Feature aggregation and update; 2 Materials and methods/2.4 Graph attention network/2.4.3 Multi-head attention for improved representation; 2 Materials and methods/2.5 Graph node representations; 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: 3d4a294aab295cbc1afd56b9ea6ced96e0717304 | 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 | RNA language model and graph attention network for RNA and small molecule binding sites prediction 2 Materials and methods/2.1 Benchmark datasets; 2 Materials and methods/2.2 Model architecture overview; 2 Materials and methods/2.3 Pre-trained RNA language model; 2 Materials and methods/2.4 Graph attention network; 2 Materials and methods/2.4 Graph attention network/2.4.1 Graph attention mechanism; 2 Materials and methods/2.4 Graph attention network/2.4.2 Feature aggregation and update; 2 Materials and methods/2.4 Graph attention network/2.4.3 Multi-head attention for improved representation; 2 Materials and methods/2.5 Graph node representations; 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: journal full text in PMC | 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
- RNA language model and graph attention network for RNA and small molecule binding sites prediction · Original source · journal full text in PMC
- SaisaiSun/RLsite README.md · Original source · 3d4a294aab295cbc1afd56b9ea6ced96e0717304
Technical metadata and extraction receipts
Stable ID: reported-model-52b9c685d99290
- areas
- rna-transcriptomes
- entity level
- method
- version
- not stated in table
- reported name
- RLsite
- historical missing metadata
- 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: rlsite-rna-binding-2025; source locator: 4 Conclusions/4.1 Hybrid architecture leveraging complementary modalities (paragraph 1); 2 Materials and methods/2.2 Model architecture overview (paragraph 1) | 2 Materials and methods/2.4 Graph attention network/2.4.2 Feature aggregation and update (paragraph 2); 1 Introduction (paragraph 7); 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.