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Author: GuangchuangYu

content/contribution-knowledge-mining.md

@@ -13,7 +13,7 @@ title: "Semantic Knowledge Mining: Methods and Applications"
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-Knowledge discovery within precision medicine big data is crucial for advancing clinical translational applications. We have established a **Semantic Knowledge Mining Framework** that bridges the gap between raw omics data and biological insights. Our contributions span the entire lifecycle of knowledge discovery: (1) **Quantifying Knowledge**: Developing semantic similarity measures to mathematically represent biological concepts; (2) **Deciphering Mechanisms**: Pioneering universal and comparative enrichment analysis methods to extract biological themes from complex experimental designs; (3) **Annotating Regulation**: Bridging genomic intervals with functional context to unlock cistromic regulation; and (4) ** integrating Prior Knowledge**: Incorporating biological priors into single-cell and spatial omics to enhance interpretability and uncover novel functional states. These methods and software tools have broadened the application of biomedical knowledge across diverse species, facilitating the mining of biological big data and the uncovering of novel discoveries.
+Knowledge discovery within precision medicine big data is crucial for advancing clinical translational applications. We have established a **Semantic Knowledge Mining Framework** that bridges the gap between raw omics data and biological insights. Our contributions span the entire lifecycle of knowledge discovery: (1) **Quantifying Knowledge**: Developing semantic similarity measures to mathematically represent biological concepts; (2) **Deciphering Mechanisms**: Pioneering universal and comparative enrichment analysis methods to extract biological themes from complex experimental designs; (3) **Annotating Regulation**: Bridging genomic intervals with functional context to unlock cistromic regulation; and (4) **Integrating Prior Knowledge**: Incorporating biological priors into single-cell and spatial omics to enhance interpretability and uncover novel functional states. These methods and software tools have broadened the application of biomedical knowledge across diverse species, facilitating the mining of biological big data and the uncovering of novel discoveries.
 
 
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