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

GENA-LM-base 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

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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-base 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	0.9545(0.0028)	Not reported	Not reported	0.9544(0.0028)	Not reported	Not reported	0.9555(0.0023)	Not reported	Not reported	0.9543(0.0029)	Not reported	Not reported
GENA-LM-base 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	0.9336(0.0021)	Not reported	Not reported	0.9337(0.0023)	Not reported	Not reported	0.9341(0.0026)	Not reported	Not reported	0.9336(0.0021)	Not reported
GENA-LM-base 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	0.9472(0.0016)	Not reported	Not reported	0.9472(0.0016)	Not reported	Not reported	0.9477(0.0012)	Not reported	Not reported	0.9472(0.0016)

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Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: GENA-LM-base 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	0.9545(0.0028) Accuracy (NT-splice-sites-acceptors, fine-tuned) fraction · higher Uncertainty: SD 0.0028 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-base 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-base', column 'Accuracy'
Configuration: GENA-LM-base 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	0.9544(0.0028) F1 (NT-splice-sites-acceptors, fine-tuned) fraction · higher Uncertainty: SD 0.0028 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-base 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-base', column 'F1 Score'
Configuration: GENA-LM-base 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	0.9555(0.0023) Precision (NT-splice-sites-acceptors, fine-tuned) fraction · higher Uncertainty: SD 0.0023 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-base 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-base', column 'Precision'
Configuration: GENA-LM-base 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	0.9543(0.0029) Recall (NT-splice-sites-acceptors, fine-tuned) fraction · higher Uncertainty: SD 0.0029 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-base 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-base', column 'Recall'
Configuration: GENA-LM-base 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	0.9336(0.0021) Accuracy (NT-splice-sites-all, fine-tuned) fraction · higher Uncertainty: SD 0.0021 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-base 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-base', column 'Accuracy'
Configuration: GENA-LM-base 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	0.9337(0.0023) F1 (NT-splice-sites-all, fine-tuned) fraction · higher Uncertainty: SD 0.0023 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-base 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-base', column 'F1 Score'
Configuration: GENA-LM-base 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	0.9341(0.0026) Precision (NT-splice-sites-all, fine-tuned) fraction · higher Uncertainty: SD 0.0026 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-base 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-base', column 'Precision'
Configuration: GENA-LM-base 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	0.9336(0.0021) Recall (NT-splice-sites-all, fine-tuned) fraction · higher Uncertainty: SD 0.0021 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-base 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-base', column 'Recall'
Configuration: GENA-LM-base 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	0.9472(0.0016) Accuracy (NT-splice-sites-donors, fine-tuned) fraction · higher Uncertainty: SD 0.0016 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-base 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-base', column 'Accuracy'
Configuration: GENA-LM-base 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	0.9472(0.0016) F1 (NT-splice-sites-donors, fine-tuned) fraction · higher Uncertainty: SD 0.0016 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-base 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-base', column 'F1 Score'
Configuration: GENA-LM-base 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	0.9477(0.0012) Precision (NT-splice-sites-donors, 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-base 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-base', column 'Precision'
Configuration: GENA-LM-base 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	0.9472(0.0016) Recall (NT-splice-sites-donors, fine-tuned) fraction · higher Uncertainty: SD 0.0016 Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source GENA-LM-base 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-base', column 'Recall'

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

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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)

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Technical metadata and extraction receipts

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

areas: dna-genomes
contexts: research
method types: foundation_model
reported name: GENA-LM-base
foundation model eligible: true
source locator: Methods, 'Construction of tissue-specific alternative splicing prediction task'; Supplementary Tables 4 and 5, row 'GENA-LM-base'
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-base 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-base on NT-splice-sites-acceptors
system: GENA-LM-base on NT-splice-sites-all
system: GENA-LM-base on NT-splice-sites-donors

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