Configuration

GENA-LM-large fine-tuned with an appended convolutional layer (You et al. 2026)

GENA-LM-large fine-tuned with an appended convolutional layer: Officially released pre-trained weights fine-tuned per task with a convolutional layer appended to the backbone; AdamW; GTEx task input divided into 500 bp blocks.

3 evaluations · 12 results

Overview

An explanatory profile has not yet been reviewed for this record.

Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.

Evaluations and results

3 evaluations · 12 results. Different protocols are not a single leaderboard.

Sorted by Accuracy (NT-splice-sites-acceptors, fine-tuned) (higher is better). The best value in each column is highlighted. Decimals are rounded for display; each value links to the printed value and its source.

Tested configuration	Protocol and dataset	Accuracy (NT-splice-sites-acceptors, fine-tuned)	Accuracy (NT-splice-sites-all, fine-tuned)	Accuracy (NT-splice-sites-donors, fine-tuned)	F1 (NT-splice-sites-acceptors, fine-tuned)	F1 (NT-splice-sites-all, fine-tuned)	F1 (NT-splice-sites-donors, fine-tuned)	Precision (NT-splice-sites-acceptors, fine-tuned)	Precision (NT-splice-sites-all, fine-tuned)	Precision (NT-splice-sites-donors, fine-tuned)	Recall (NT-splice-sites-acceptors, fine-tuned)	Recall (NT-splice-sites-all, fine-tuned)	Recall (NT-splice-sites-donors, fine-tuned)
GENA-LM-large fine-tuned with an appended convolutional layer (You et al. 2026)Evaluation	NT-splice-sites-acceptors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4), Nucleotide Transformer benchmark splice-site dataset, acceptors	0.9618(0.0011)	Not reported	Not reported	0.9618(0.0011)	Not reported	Not reported	0.9621(0.0011)	Not reported	Not reported	0.9618(0.0012)	Not reported	Not reported
GENA-LM-large fine-tuned with an appended convolutional layer (You et al. 2026)Evaluation	NT-splice-sites-all splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4), Nucleotide Transformer benchmark splice-site dataset, all sites	Not reported	0.9482(0.0032)	Not reported	Not reported	0.9483(0.0030)	Not reported	Not reported	0.9488(0.0025)	Not reported	Not reported	0.9482(0.0032)	Not reported
GENA-LM-large fine-tuned with an appended convolutional layer (You et al. 2026)Evaluation	NT-splice-sites-donors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4), Nucleotide Transformer benchmark splice-site dataset, donors	Not reported	Not reported	0.9595(0.0005)	Not reported	Not reported	0.9595(0.0005)	Not reported	Not reported	0.9596(0.0005)	Not reported	Not reported	0.9595(0.0005)

All 12 result rows with coverage, uncertainty and sources

Filter evaluations

Tested model or methodProtocolDatasetEvaluation setupMetricEvidence origin

Applied filters: All linked evaluations

Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: GENA-LM-large fine-tuned with an appended convolutional layer (You et al. 2026)	Protocol: NT-splice-sites-acceptors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4) Dataset: Nucleotide Transformer benchmark splice-site dataset, acceptors	0.9618(0.0011) Accuracy (NT-splice-sites-acceptors, fine-tuned) fraction · higher Uncertainty: SD 0.0011 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-large on NT-splice-sites-acceptors gfm2-20261011-you2026-protocol-nt-splice-acceptors Aggregation: Not reported Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications; You et al. 2026, Supplementary Information · Supplementary Table 4, block 'NT-splice-sites-acceptors', row 'GENA-LM-large', column 'Accuracy'
Configuration: GENA-LM-large fine-tuned with an appended convolutional layer (You et al. 2026)	Protocol: NT-splice-sites-acceptors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4) Dataset: Nucleotide Transformer benchmark splice-site dataset, acceptors	0.9618(0.0011) F1 (NT-splice-sites-acceptors, fine-tuned) fraction · higher Uncertainty: SD 0.0011 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-large on NT-splice-sites-acceptors gfm2-20261011-you2026-protocol-nt-splice-acceptors Aggregation: Not reported Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications; You et al. 2026, Supplementary Information · Supplementary Table 4, block 'NT-splice-sites-acceptors', row 'GENA-LM-large', column 'F1 Score'
Configuration: GENA-LM-large fine-tuned with an appended convolutional layer (You et al. 2026)	Protocol: NT-splice-sites-acceptors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4) Dataset: Nucleotide Transformer benchmark splice-site dataset, acceptors	0.9621(0.0011) Precision (NT-splice-sites-acceptors, fine-tuned) fraction · higher Uncertainty: SD 0.0011 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-large on NT-splice-sites-acceptors gfm2-20261011-you2026-protocol-nt-splice-acceptors Aggregation: Not reported Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications; You et al. 2026, Supplementary Information · Supplementary Table 4, block 'NT-splice-sites-acceptors', row 'GENA-LM-large', column 'Precision'
Configuration: GENA-LM-large fine-tuned with an appended convolutional layer (You et al. 2026)	Protocol: NT-splice-sites-acceptors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4) Dataset: Nucleotide Transformer benchmark splice-site dataset, acceptors	0.9618(0.0012) Recall (NT-splice-sites-acceptors, fine-tuned) fraction · higher Uncertainty: SD 0.0012 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-large on NT-splice-sites-acceptors gfm2-20261011-you2026-protocol-nt-splice-acceptors Aggregation: Not reported Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications; You et al. 2026, Supplementary Information · Supplementary Table 4, block 'NT-splice-sites-acceptors', row 'GENA-LM-large', column 'Recall'
Configuration: GENA-LM-large fine-tuned with an appended convolutional layer (You et al. 2026)	Protocol: NT-splice-sites-all splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4) Dataset: Nucleotide Transformer benchmark splice-site dataset, all sites	0.9482(0.0032) Accuracy (NT-splice-sites-all, fine-tuned) fraction · higher Uncertainty: SD 0.0032 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-large on NT-splice-sites-all gfm2-20261011-you2026-protocol-nt-splice-all Aggregation: Not reported Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications; You et al. 2026, Supplementary Information · Supplementary Table 4, block 'NT-splice-sites-all', row 'GENA-LM-large', column 'Accuracy'
Configuration: GENA-LM-large fine-tuned with an appended convolutional layer (You et al. 2026)	Protocol: NT-splice-sites-all splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4) Dataset: Nucleotide Transformer benchmark splice-site dataset, all sites	0.9483(0.0030) F1 (NT-splice-sites-all, fine-tuned) fraction · higher Uncertainty: SD 0.0030 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-large on NT-splice-sites-all gfm2-20261011-you2026-protocol-nt-splice-all Aggregation: Not reported Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications; You et al. 2026, Supplementary Information · Supplementary Table 4, block 'NT-splice-sites-all', row 'GENA-LM-large', column 'F1 Score'
Configuration: GENA-LM-large fine-tuned with an appended convolutional layer (You et al. 2026)	Protocol: NT-splice-sites-all splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4) Dataset: Nucleotide Transformer benchmark splice-site dataset, all sites	0.9488(0.0025) Precision (NT-splice-sites-all, fine-tuned) fraction · higher Uncertainty: SD 0.0025 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-large on NT-splice-sites-all gfm2-20261011-you2026-protocol-nt-splice-all Aggregation: Not reported Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications; You et al. 2026, Supplementary Information · Supplementary Table 4, block 'NT-splice-sites-all', row 'GENA-LM-large', column 'Precision'
Configuration: GENA-LM-large fine-tuned with an appended convolutional layer (You et al. 2026)	Protocol: NT-splice-sites-all splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4) Dataset: Nucleotide Transformer benchmark splice-site dataset, all sites	0.9482(0.0032) Recall (NT-splice-sites-all, fine-tuned) fraction · higher Uncertainty: SD 0.0032 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-large on NT-splice-sites-all gfm2-20261011-you2026-protocol-nt-splice-all Aggregation: Not reported Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications; You et al. 2026, Supplementary Information · Supplementary Table 4, block 'NT-splice-sites-all', row 'GENA-LM-large', column 'Recall'
Configuration: GENA-LM-large fine-tuned with an appended convolutional layer (You et al. 2026)	Protocol: NT-splice-sites-donors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4) Dataset: Nucleotide Transformer benchmark splice-site dataset, donors	0.9595(0.0005) Accuracy (NT-splice-sites-donors, fine-tuned) fraction · higher Uncertainty: SD 0.0005 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-large on NT-splice-sites-donors gfm2-20261011-you2026-protocol-nt-splice-donors Aggregation: Not reported Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications; You et al. 2026, Supplementary Information · Supplementary Table 4, block 'NT-splice-sites-donors', row 'GENA-LM-large', column 'Accuracy'
Configuration: GENA-LM-large fine-tuned with an appended convolutional layer (You et al. 2026)	Protocol: NT-splice-sites-donors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4) Dataset: Nucleotide Transformer benchmark splice-site dataset, donors	0.9595(0.0005) F1 (NT-splice-sites-donors, fine-tuned) fraction · higher Uncertainty: SD 0.0005 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-large on NT-splice-sites-donors gfm2-20261011-you2026-protocol-nt-splice-donors Aggregation: Not reported Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications; You et al. 2026, Supplementary Information · Supplementary Table 4, block 'NT-splice-sites-donors', row 'GENA-LM-large', column 'F1 Score'
Configuration: GENA-LM-large fine-tuned with an appended convolutional layer (You et al. 2026)	Protocol: NT-splice-sites-donors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4) Dataset: Nucleotide Transformer benchmark splice-site dataset, donors	0.9596(0.0005) Precision (NT-splice-sites-donors, fine-tuned) fraction · higher Uncertainty: SD 0.0005 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-large on NT-splice-sites-donors gfm2-20261011-you2026-protocol-nt-splice-donors Aggregation: Not reported Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications; You et al. 2026, Supplementary Information · Supplementary Table 4, block 'NT-splice-sites-donors', row 'GENA-LM-large', column 'Precision'
Configuration: GENA-LM-large fine-tuned with an appended convolutional layer (You et al. 2026)	Protocol: NT-splice-sites-donors splice-site classification, fine-tuned models (You et al. 2026 Supplementary Table 4) Dataset: Nucleotide Transformer benchmark splice-site dataset, donors	0.9595(0.0005) Recall (NT-splice-sites-donors, fine-tuned) fraction · higher Uncertainty: SD 0.0005 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-large on NT-splice-sites-donors gfm2-20261011-you2026-protocol-nt-splice-donors Aggregation: Not reported Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications; You et al. 2026, Supplementary Information · Supplementary Table 4, block 'NT-splice-sites-donors', row 'GENA-LM-large', column 'Recall'

Source checking is not independent reproduction. Release 2026-10-22-1b7cf027e4f6.

Use this configuration

How it works, versions and access

Strengths, limitations and unresolved questions

Evidence

Source checking verifies the cited claim or transcription. It does not establish independent reproduction.

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.

0 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-10-22-1b7cf027e4f6
Property and statement	Original source and location	Review and provenance

No evidence rows match these filters. Choose another scope or clear the search.

How to read the evidence

Sources and history

Release 2026-10-22-1b7cf027e4f6 · Record review: source checked

2 source records and release history

Benchmarking pre-trained genomic language models for RNA sequence-related predictive applications · Original source · Nat Commun 17:223, published online 2025-12-07; PMC12780105 full-text XML
You et al. 2026, Supplementary Information · Original source · 41467_2025_66899_MOESM1_ESM.pdf inside the Europe PMC supplementaryFiles zip (outer zip 9a0d0a8d8643872ab265e3e6ed7eea944563da4861bf764f97c68fc6aa502525, assembled per request; the member hash is the bound artifact)

Download this release (gzip)

Technical metadata and extraction receipts

Stable ID: gfm2-20261011-you2026-config-gena-lm-large

areas: dna-genomes
contexts: research
method types: foundation_model
reported name: GENA-LM-large
foundation model eligible: true
source locator: Methods, 'Construction of tissue-specific alternative splicing prediction task'; Supplementary Tables 4 and 5, row 'GENA-LM-large'
parameters: Officially released pre-trained weights fine-tuned per task with a convolutional layer appended to the backbone (Methods); AdamW; parameters in Supplementary Table 1; GTEx task input divided into 500 bp blocks; fine-tuned and tested three times with different random initialisations
missing metadata: version: reason: unreported; note: Checkpoint revision not printed; fine-tuning parameters are in Supplementary Table 1
training setting: Fine-tuned on the task training split
provenance note: GENA-LM-large fine-tuned with an appended convolutional layer (You et al. 2026), as evaluated in the cited comparison.

Related records

configuration of: GENA-LM
system: GENA-LM-large on NT-splice-sites-acceptors
system: GENA-LM-large on NT-splice-sites-all
system: GENA-LM-large on NT-splice-sites-donors

Suggest a correction