Cancer research generates an enormous amount of data. Hidden inside that data are clues that can help researchers better understand why childhood cancers develop, how they behave, and which treatments may work best.
At the Greehey Children’s Cancer Research Institute, the Chen Lab, led by Yidong Chen, PhD, uses computational biology, bioinformatics and biostatistics to turn complex genomic information into useful discoveries.
Think of it as finding meaningful patterns in a massive biological puzzle.
Dr. Chen and his team develop computational tools to analyze DNA and RNA, study gene regulation, and examine molecular differences among cancers. Their work includes machine learning and deep learning, cancer genome profiling, drug-response prediction, and precision medicine.
For childhood cancer research, those capabilities can help scientists identify genetic changes driving a tumor, understand why cancers respond differently to treatment and uncover vulnerabilities that could point toward better therapies. The lab has contributed genomic analyses to research involving pediatric cancers including hepatoblastoma, soft-tissue sarcomas and Ewing sarcoma.
Because sometimes the next breakthrough begins by finding the right signal among millions of pieces of data.
Better data can lead to better questions—and ultimately, better answers for children with cancer.
🔬 Learn more about the Chen Lab