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  ## 📑 Dataset Summary
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  **Target-QA** is derived from the **DepMap** multi-omics and CRISPR screening cohorts, harmonized via **[BioMedGraphica](https://huggingface.co/datasets/FuhaiLiAiLab/BioMedGraphica)**.
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- It enables **multi-modal reasoning** by combining quantitative omics, biomedical knowledge graphs, and disease annotations for **CRISPR target prioritization**.
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  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.
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  - 🔗 Source code: [GitHub](https://github.com/FuhaiLiAiLab/GALAX)
 
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  ## 📑 Dataset Summary
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  **Target-QA** is derived from the **DepMap** multi-omics and CRISPR screening cohorts, harmonized via **[BioMedGraphica](https://huggingface.co/datasets/FuhaiLiAiLab/BioMedGraphica)**.
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+ It enables **multi-modal reasoning** by combining numeric evidence, topological knowledge and language context for **CRISPR target prioritization**.
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  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.
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  - 🔗 Source code: [GitHub](https://github.com/FuhaiLiAiLab/GALAX)