Strengths and considerations
No source-reviewed explanatory claims are recorded here yet.
model · method
DNABERT2-Enhancer
DNABERT2-Enhancer is the method recorded for enhancer recognition. This page preserves the configuration reported by Utilizing a deep learning model based on BERT for identifying enhancers and their strength.
At a glance
Explanatory profile: limited source coverage · Automated source review, 2026-09-16. This does not change the review status of its results.
| Property | Description and evidence |
|---|---|
| Recorded dataset | Liu training datasetUtilizing a deep learning model based on BERT for identifying enhancers and their strength · Table 4, first-layer DNABERT2-Enhancer row, AUC column |
| Recorded split | 5-fold cross-validationUtilizing a deep learning model based on BERT for identifying enhancers and their strength · Table 4, first-layer DNABERT2-Enhancer row, AUC column |
| Recorded configuration | not stated in tableUtilizing a deep learning model based on BERT for identifying enhancers and their strength · Table 4, first-layer DNABERT2-Enhancer row, AUC column |
| Model type | Not extracted or verified for this record. |
| Training data | Not extracted or verified for this record. |
| Context limits | Not extracted or verified for this record. |
| Access | Not extracted or verified for this record. |
| Code licence | Not extracted or verified for this record. |
| Weights licence | Not extracted or verified for this record. |
How it works
Recorded evaluation
The imported evaluation describes this procedure: first-layer enhancer versus non-enhancer classifier
Utilizing a deep learning model based on BERT for identifying enhancers and their strength · Table 4, first-layer DNABERT2-Enhancer row, AUC columnBenchmarks and results
Release 2026-09-16-d74d282221a9 · 1 evaluation · 1 metric row. Different protocols are not a single leaderboard.
| Metric and finding | Coverage and uncertainty | Evidence |
|---|---|---|
| DNABERT2-Enhancer: enhancer recognition first-layer enhancer versus non-enhancer classifier Author-reported evaluation · Evaluation metadata: needs review | ||
| 0.965 AUC Unit: fraction · Direction: unknown | Uncertainty: not reported in legacy extract Scored: Not reported · Eligible: Not reported | source checkedUtilizing a deep learning model based on BERT for identifying enhancers and their strength · Table 4, first-layer DNABERT2-Enhancer row, AUC column Source checking is not independent reproduction. |
Strengths and limitations
Limitations and conditions
- This is an evidence-limited profile. The recorded evaluation context does not establish performance on other datasets or configurations.Utilizing a deep learning model based on BERT for identifying enhancers and their strength · Table 4, first-layer DNABERT2-Enhancer row, AUC column
Profile review details
Reviewed the existing release record, its source pointer and linked evaluation context. This is not a fresh full-text architecture review or independent reproduction; numerical review status is unchanged.
Stable record: reported-model-d0e594ec3c0430Sources and history
Release 2026-09-16-d74d282221a9 · Record review: needs review
- Utilizing a deep learning model based on BERT for identifying enhancers and their strength · Original source · journal full text in PMC
Technical metadata and extraction receipts
Stable ID: reported-model-d0e594ec3c0430
- areas
- dna-genomes
- entity level
- method
- version
- not stated in table
- reported name
- DNABERT2-Enhancer
- missing metadata
- checkpoint revision: not_reported_in_legacy_extract; training data: not_reported_in_legacy_extract; licence: not_reported_in_legacy_extract