| Abstract |
This project explores Urolithin A’s transcriptional properties in CRC and their significance in CRC microenvironment cell heterogeneity to identify potential biomarkers like key differentially expressed genes or ligand-receptor pairs. By integrating scRNA-seq data alongside transcriptomic analysis, and leveraging AI and large language models, it aims to enhance experimental efficiency, accelerate analysis, reduce costs, and support precision medicine for early CRC detection and future targeted treatments. |
