updated

README.md

@@ -9730,13 +9730,24 @@ model-index:
 
 # DeepVRegulome
 
-**462 fine-tuned DNABERT models for regulatory variant effect prediction**
+<p align="center">
+  <a href="https://github.com/DavuluriLab/DeepVRegulome"><img src="https://img.shields.io/badge/GitHub-Repo-181717?logo=github" alt="GitHub"></a>
+  <a href="https://pypi.org/project/deepvregulome/"><img src="https://img.shields.io/pypi/v/deepvregulome?color=blue" alt="PyPI"></a>
+  <a href="https://pepy.tech/projects/deepvregulome"><img src="https://static.pepy.tech/personalized-badge/deepvregulome?period=total&units=INTERNATIONAL_SYSTEM&left_color=BLACK&right_color=GREEN&left_text=downloads" alt="PyPI Downloads"></a>
+  <a href="https://huggingface.co/spaces/duttaprat/DeepVRegulome"><img src="https://img.shields.io/badge/%F0%9F%A4%97-Live%20Demo-blue" alt="HuggingFace Space"></a>
+  <a href="https://arxiv.org/abs/2511.09026"><img src="https://img.shields.io/badge/arXiv-2511.09026-b31b1b" alt="arXiv"></a>
+  <a href="https://deepvregulome.streamlit.app"><img src="https://img.shields.io/badge/demo-Streamlit-ff4b4b" alt="Streamlit"></a>
+  <a href="https://creativecommons.org/licenses/by-nc/4.0/"><img src="https://img.shields.io/badge/license-CC--BY--NC--4.0-green" alt="License"></a>
+</p>
+
+**464 fine-tuned DNABERT models for regulatory variant effect prediction**
 
 DeepVRegulome is an end-to-end framework for predicting the functional impact
 of small somatic variants in non-coding regulatory regions using fine-tuned
 [DNABERT](https://github.com/jerryji1993/DNABERT) models. It covers **458
-transcription factors** and **4 histone modifications** from ENCODE ChIP-seq data,
-validated against Yan et al. (2021) SNP-SELEX experimental variant-effect measurements.
+transcription factors**, **4 histone modifications**, and **2 splice sites**
+(acceptor + donor) from ENCODE ChIP-seq and GENCODE data, validated against
+Yan et al. (2021) SNP-SELEX experimental variant-effect measurements.
 
 | Resource | Link |
 |----------|------|
@@ -9744,10 +9755,12 @@ validated against Yan et al. (2021) SNP-SELEX experimental variant-effect measur
 | Code | [GitHub: DavuluriLab/DeepVRegulome](https://github.com/DavuluriLab/DeepVRegulome) |
 | PyPI | `pip install deepvregulome` |
 | Web App | [deepvregulome.streamlit.app](https://deepvregulome.streamlit.app) |
+| Live Demo | [HuggingFace Space](https://huggingface.co/spaces/duttaprat/DeepVRegulome) |
 
 ## Key Features
 
-- **462 fine-tuned models** (458 TF-binding + 4 histone mark) trained on ENCODE ChIP-seq peaks
+- **464 fine-tuned models** (458 TF-binding + 4 histone mark + 2 splice-site) trained on ENCODE ChIP-seq peaks and GENCODE exon-intron junctions
+- **Splice-site disruption scoring** for acceptor (3') and donor (5') junction variants
 - **Variant effect scoring** via log-odds ratio between reference and alternate alleles
 - **Attention-based motif analysis** for interpretable predictions
 - **Experimentally validated** against SNP-SELEX (Yan et al., 2021, Nature Genetics): mean per-TF AUROC = 0.611 across 61 evaluable TFs