Update README.md

README.md

@@ -1,16 +1,69 @@
-# Target-QA: QA Dataset Based on DepMap Multi-Omics Profiles and CRISPR Outcomes
+---
+annotations_creators: []
+language:
+- en
+license: mit
+multilinguality: []
+pretty_name: Target-QA
+size_categories:
+- n<1K
+source_datasets:
+- depmap
+- biomedgraphica
+tags:
+- bioinformatics
+- graph-ml
+- precision-medicine
+task_categories:
+- question-answering
+- text-generation
+task_ids:
+- extractive-qa
+- text2text-generation
+paperswithcode_id: null
+---
+
+
+# 🎯 Target-QA: The First QA Dataset Benchmarking Target Priorization Based on DepMap
+
+<div align="center" style="line-height: 1.4;">
+
+  <!-- arXiv -->
+  <a href="https://arxiv.org/abs/2509.20935" target="_blank" style="margin: 2px;">
+    <img alt="arXiv" src="https://img.shields.io/badge/arXiv-GALAX%20Paper-b31b1b?logo=arxiv&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
+  </a>
 
-## Dataset Summary  
+  <!-- Hugging Face Dataset -->
+  <a href="https://huggingface.co/datasets/FuhaiLiAiLab/Target-QA" target="_blank" style="margin: 2px;">
+    <img alt="Hugging Face Dataset" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Target--QA%20Dataset-ff6f61?color=ffc107&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
+  </a>
+  
+  <!-- GitHub -->
+  <a href="https://github.com/FuhaiLiAiLab/GALAX" target="_blank" style="margin: 2px;">
+    <img alt="GitHub" src="https://img.shields.io/badge/GitHub-GALAX%20Code-181717?logo=github&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
+  </a>
 
-**Target-QA** is a dataset constructed from the **DepMap** multi-omics and CRISPR screening cohorts, harmonized via **[BioMedGraphica](https://huggingface.co/datasets/FuhaiLiAiLab/BioMedGraphica)**.  
+  <!-- Hugging Face Model -->
+  <a href="https://huggingface.co/FuhaiLiAiLab/GALAX" target="_blank" style="margin: 2px;">
+    <img alt="Hugging Face Model" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-GALAX%20Model-ffc107?color=ffc107&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
+  </a>
+
+</div>
+
+---
+
+## 📑 Dataset Summary  
+
+**Target-QA** is derived from the **DepMap** multi-omics and CRISPR screening cohorts, harmonized via **[BioMedGraphica](https://huggingface.co/datasets/FuhaiLiAiLab/BioMedGraphica)**.  
 It enables **multi-modal reasoning** by combining quantitative omics, biomedical knowledge graphs, and disease annotations for **CRISPR target prioritization**.  
 
-The dataset is designed for training and benchmarking **graph-augmented large language models (LLMs)**, such as **GALAX**, that reason over both structured and unstructured biological information.
-And GALAX source code is available at [GitHub link](https://github.com/FuhaiLiAiLab/GALAX) and parameters is available at [HuggingFace repo](https://huggingface.co/FuhaiLiAiLab/GALAX).
+This dataset supports the training and benchmarking of **graph-augmented large language models (LLMs)**, such as **[GALAX](https://huggingface.co/FuhaiLiAiLab/GALAX)**, for reasoning across structured and unstructured biomedical information.  
+- 🔗 Source code: [GitHub](https://github.com/FuhaiLiAiLab/GALAX)  
+- 🤗 Model parameters: [Hugging Face](https://huggingface.co/FuhaiLiAiLab/GALAX)  
 
 ---
 
-## Preprocessing Details  
+## 🛠️ Preprocessing Details  
 
 ![Dataset composition and splits](./FigureS1.png)
 
@@ -27,11 +80,9 @@ And GALAX source code is available at [GitHub link](https://github.com/FuhaiLiAi
   - Protein–protein interactions: 17,151,453 edges  
   - Disease–target associations: 27,087,971 edges  
 
-> **Note:** Methylation values excluded due to high saturation.  
-
 ---
 
-## Data Splits  
+## 📂 Data Splits  
 
 - **Pretraining set**: 336 samples  
   - Train: 269  
@@ -44,19 +95,15 @@ And GALAX source code is available at [GitHub link](https://github.com/FuhaiLiAi
 
 ---
 
+## 🧪 Supported Tasks & Benchmarks  
 
-## Supported Tasks and Benchmarks  
-
-- **Graph-Augmented Question Answering**  
-  - Identify CRISPR targets given omics and KG context.  
-- **Knowledge Graph Reasoning**  
-  - Subgraph extraction and signaling network prioritization.  
-- **Multi-Omic Target Prioritization**  
-  - Integration of genomic, transcriptomic, and proteomic data.   
+- **Graph-Augmented QA**: Identify CRISPR targets from omics + KG context  
+- **Knowledge Graph Reasoning**: Subgraph extraction & signaling network prioritization  
+- **Multi-Omic Target Prioritization**: Genomic, transcriptomic, proteomic integration  
 
 ---
 
-## Dataset Structure  
+## 📊 Dataset Structure  
 
 ### Example JSON  
 
@@ -87,24 +134,9 @@ And GALAX source code is available at [GitHub link](https://github.com/FuhaiLiAi
     "protein_llmname_ids": ["ENSP00000439978"]
   }
 }
-
 ```
 
-## Data Fields  
-
-- **cell_line_name**: Cell line name *(string)*  
-- **cell_line_id**: DepMap identifier *(string)*  
-- **disease**: Disease name *(string)*  
-- **disease_bmgc_id**: BioMedGraphica disease ID *(string)*  
-- **sample_dti_index**: Omics index for NumPy array access *(int)*  
-- **input**: Multi-modal context  
-  - Top-k genes, transcripts, proteins (HGNC, BioMedGraphica IDs, synonyms)  
-  - Knowledge graph neighbors, PPIs, disease–protein associations  
-- **ground_truth_answer**: CRISPR-validated targets (HGNC, BioMedGraphica IDs, synonyms)  
-
----
-
-## Prompt Design  
+## 📝 Prompt Design  
 
 ### Initial Prompt (`P_init_n`)  
 
@@ -120,22 +152,36 @@ And GALAX source code is available at [GitHub link](https://github.com/FuhaiLiAi
 
 **Inputs:**  
 - Same as above  
-- + Subsignaling gene regulatory network (from graph generator)  
+- Subsignaling gene regulatory network (from graph generator)  
 
 **Output:**  
 - Refined 100 vulnerability genes `r_hat[n,1...100]`  
 
 ---
 
-## Licensing  
+## ⚖️ Licensing  
 
 This dataset is based on **DepMap** data and is subject to the **DepMap Terms of Use**:  
 - Free for **research purposes only**  
-- **Commercial use prohibited** without explicit license from Broad Institute or contributors  
-- Machine learning models may be trained **for internal research use** or shared **for non-profit research purposes**  
+- **Commercial use prohibited** without explicit Broad Institute license  
+- ML models may be trained for **internal research use** or shared for **non-profit research**  
 - Attribution to **Broad Institute / DepMap** is required  
 
-**DepMap Terms of Use:** [https://depmap.org/portal/](https://depmap.org/portal/)  
+🔗 [DepMap Terms of Use](https://depmap.org/portal)  
 
-**Acknowledgment:**  
-This dataset is derived from the Broad Institute’s Cancer Dependency Map (DepMap) and will be released strictly for non-commercial, internal research and academic use, consistent with DepMap’s Terms of Use. We do not redistribute original DepMap files; instead, we provide derived, non-identifiable annotations and processing scripts/pointers so users can obtain the source data directly from DepMap after accepting its terms. The dataset is not intended for clinical applications and must not be used for any Commercial Use (e.g., direct sale, incorporation into a product, or training/developing/enhancing ML/AI models beyond internal academic research). Users agree to acknowledge DepMap and the Broad Institute using the acknowledgement wording specified by DepMap, and to respect any third-party rights that may attach to the underlying data. Users must preserve confidentiality and refrain from any re-identification attempts. This statement summarizes our compliance posture and does not constitute legal advice; users are responsible for ensuring their own compliance with DepMap’s Terms and applicable policies.
+---
+
+## 📚 Citation  
+
+If you use **Target-QA** or **GALAX**, please cite:  
+
+```bibtex
+@misc{zhang2025galax,
+  title={GALAX: Graph-Augmented Language Model for Explainable Reinforcement-Guided Subgraph Reasoning in Precision Medicine},
+  author={Heming Zhang and Di Huang and Wenyu Li and Michael Province and Yixin Chen and Philip Payne and Fuhai Li},
+  year={2025},
+  eprint={2509.20935},
+  archivePrefix={arXiv},
+  primaryClass={cs.AI},
+  url={https://arxiv.org/abs/2509.20935}
+}