Upload 21 files

.gitattributes

@@ -60,3 +60,13 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
 CTCF_TF/CTCF_TF_train.csv filter=lfs diff=lfs merge=lfs -text
 CTCF_TF/CTCF_TF.csv filter=lfs diff=lfs merge=lfs -text
+H3k27ac/H3k27ac_train.csv filter=lfs diff=lfs merge=lfs -text
+H3k27ac/H3k27ac.csv filter=lfs diff=lfs merge=lfs -text
+H3K27me3/H3K27me3_train.csv filter=lfs diff=lfs merge=lfs -text
+H3K27me3/H3K27me3.csv filter=lfs diff=lfs merge=lfs -text
+H3K4me1/H3K4me1_train.csv filter=lfs diff=lfs merge=lfs -text
+H3K4me1/H3K4me1.csv filter=lfs diff=lfs merge=lfs -text
+H3K4me3/H3K4me3_train.csv filter=lfs diff=lfs merge=lfs -text
+H3K4me3/H3K4me3.csv filter=lfs diff=lfs merge=lfs -text
+H3K9me3/H3K9me3_train.csv filter=lfs diff=lfs merge=lfs -text
+H3K9me3/H3K9me3.csv filter=lfs diff=lfs merge=lfs -text

H3K27me3/H3K27me3.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0b0ca11c0d142691ef2389e00c0a43eff69b81317cfba5b7e8009d77cd671f8a
+size 26405838

H3K27me3/H3K27me3_train.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b3815dbd32e3a71c986cefbed1264f76ca7b9a545c2a458d01509ea6ef855d38
+size 21028029

H3K4me1/H3K4me1.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5f23c2767941dee71d299c68a7e2000aef97e5eef9fdd9ce7ee492d5a3402f77
+size 40891878

H3K4me1/H3K4me1_train.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:15b1f672301ee4227221bececf212a782dbe80d1f31de4d4e6dd56d8d4f3aeaa
+size 32719682

H3K4me3/H3K4me3.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9573a6fa07fcdda6112a2491149c3bcfdde32d7ee457a3701cc0aeb272906ab5
+size 40605734

H3K4me3/H3K4me3_train.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:12478d4283fc45000d82f3adda9c53dbf5d36dad6320dd3d778033c55bd357f3
+size 32488858

H3K9me3/H3K9me3.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bf4d7950acd51580d3835be7c2fe9354fa4e2fbc9e439a116d2cc591411bfeca
+size 61286732

H3K9me3/H3K9me3_train.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:87282842b73ce243b51eb6879b07af0de9c35206b4be4d9d224c0c14cb063a16
+size 49015705

H3k27ac/H3k27ac.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7e9f3cbb3f4cab7c66e895ea0a99106d784c8e0f829f58dcbc520749a28ea1cf
+size 25736530

H3k27ac/H3k27ac_train.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:813ee806e8cb4a0a137fbc68a1db9086ba91c5b1a42b4072c2f7f7a35f1de413
+size 20567354

README.md

@@ -1,3 +1,137 @@
----
-license: cc-by-nc-4.0
----
+---
+license: cc-by-nc-4.0
+task_categories:
+- text-classification
+language:
+- en
+tags:
+- genomics
+- fish
+- DNA
+- benchmark
+- promoter
+- splice-site
+- transcription-factor-binding-site
+- histone-mark
+size_categories:
+- 100K<n<1M
+pretty_name: FishGUE
+---
+
+# FishGUE
+
+**FishGUE** is a unified fish genomics benchmark developed for evaluating DNA foundation models and other sequence models on fish genomic prediction tasks.
+
+It was introduced in the FishNALM study, where it was used to systematically benchmark fish-specific and general DNA language models across diverse regulatory sequence prediction tasks.
+
+## Dataset summary
+
+FishGUE contains **17 supervised prediction tasks** spanning four task groups:
+
+- **Histone mark prediction**
+- **Transcription factor binding-site prediction**
+- **Promoter prediction**
+- **Splice-site prediction**
+
+The benchmark covers input sequence lengths from **300 bp to 2500 bp** and includes both **zebrafish-based datasets** and **multi-species cyprinid splice datasets**.
+
+## Why FishGUE?
+
+Fish genomic benchmarks remain limited compared with those available for human, plant, or broad multi-species genomic modeling. FishGUE was constructed to provide a unified benchmark for evaluating model performance on representative fish genomic sequence prediction problems, especially those relevant to regulatory sequence recognition and gene structure annotation.
+
+## Benchmark composition
+
+The FishGUE benchmark includes the following 17 tasks.
+
+| Category | Task | Species | Sequence length (bp) | Train / Val / Test |
+|---|---|---|---:|---:|
+| Histone mark prediction | H3K4me1 | *Danio rerio* | variable (≤2500) | 48815 / 6102 / 6102 |
+| Histone mark prediction | H3K4me3 | *Danio rerio* | variable (≤2500) | 47482 / 5935 / 5936 |
+| Histone mark prediction | H3K9me3 | *Danio rerio* | variable (≤2500) | 40125 / 5016 / 5016 |
+| Histone mark prediction | H3K27ac | *Danio rerio* | variable (≤2500) | 27611 / 3451 / 3452 |
+| Histone mark prediction | H3K27me3 | *Danio rerio* | variable (≤2500) | 27017 / 3377 / 3378 |
+| TF binding-site prediction | CTCF | *Danio rerio* | 800 | 28526 / 3566 / 3566 |
+| TF binding-site prediction | Pou5f1 | *Danio rerio* | 800 | 11128 / 1391 / 1391 |
+| TF binding-site prediction | Sox2 | *Danio rerio* | 800 | 9717 / 1215 / 1215 |
+| Promoter prediction | Core promoter | *Danio rerio* | 300 | 17222 / 2153 / 2153 |
+| Promoter prediction | Core promoter (TATA) | *Danio rerio* | 300 | 3464 / 433 / 434 |
+| Promoter prediction | Core promoter (non-TATA) | *Danio rerio* | 300 | 13757 / 1720 / 1720 |
+| Promoter prediction | Promoter | *Danio rerio* | 1000 | 17222 / 2153 / 2153 |
+| Promoter prediction | Promoter (TATA) | *Danio rerio* | 1000 | 3464 / 433 / 434 |
+| Promoter prediction | Promoter (non-TATA) | *Danio rerio* | 1000 | 13757 / 1720 / 1720 |
+| Splice-site prediction | Splicing (acceptor) | Cyprinidae (5 species) | 600 | 17200 / 2150 / 2150 |
+| Splice-site prediction | Splicing (donor) | Cyprinidae (5 species) | 600 | 27600 / 3450 / 3450 |
+| Splice-site prediction | Splicing (both) | Cyprinidae (5 species) | 600 | 1720 / 2150 / 2105 |
+
+## Data sources and construction overview
+
+According to the FishNALM manuscript, FishGUE was assembled from the following sources:
+
+- **Histone mark datasets** were derived from public zebrafish ChIP-seq peak datasets.
+- **Transcription factor binding-site datasets** were built from public ChIP-seq peaks for **CTCF**, **Pou5f1**, and **Sox2**.
+- **Promoter datasets** were constructed from zebrafish promoter annotations from the **Eukaryotic Promoter Database (EPD)**.
+- **Splice-site datasets** were compiled from annotated genomes of **five cyprinid fish species**.
+
+For all tasks, positive and negative examples were constructed through task-specific processing, then split into **training**, **validation**, and **test** sets using an **8:1:1** ratio.
+
+## Suggested repository organization
+
+If you plan to upload FishGUE as a single Hugging Face dataset repository, a clean structure is:
+
+```text
+FishGUE/
+├── README.md
+├── histone/
+│   ├── H3K4me1_train.tsv
+│   ├── H3K4me1_val.tsv
+│   ├── H3K4me1_test.tsv
+│   └── ...
+├── tfbs/
+│   ├── CTCF_train.tsv
+│   ├── CTCF_val.tsv
+│   ├── CTCF_test.tsv
+│   └── ...
+├── promoter/
+│   ├── core_promoter_300_train.tsv
+│   └── ...
+└── splice/
+    ├── splice_acceptor_train.tsv
+    └── ...
+```
+
+If your files are already packaged in another layout, you can keep that layout and simply explain it in this README.
+
+## Intended uses
+
+FishGUE is intended for:
+
+- benchmarking DNA foundation models on fish genomic sequence prediction tasks
+- evaluating transfer learning performance in fish genomics
+- comparing task robustness across promoter, chromatin, TFBS, and splice-site prediction settings
+- developing new fish-specific sequence models and downstream classifiers
+
+## Limitations
+
+- Most non-splice tasks are based on **zebrafish** data.
+- The splice-site benchmark uses **five cyprinid species**, so broader phylogenetic coverage remains limited.
+- FishGUE is designed as a **research benchmark** and should not be interpreted as a clinical or diagnostic dataset.
+- Performance on FishGUE does not guarantee performance on all fish species or all regulatory genomics tasks.
+
+## Citation
+
+If you use FishGUE in your work, please cite the FishNALM manuscript.
+
+**Manuscript:**
+
+> FishNALM: A Foundation DNA Language Model for Fish Genomes
+
+## Project links
+
+- **GitHub**: [bioinfoihb/FishNALM](https://github.com/bioinfoihb/FishNALM)
+
+## Contact
+
+**Xiao-Qin Xia**  
+Institute of Hydrobiology, Chinese Academy of Sciences  
+Email: xqxia@ihb.ac.cn  
+Email: bioinfoihb@ihb.ac.cn