We apply computational biology and bioinformatics to understand how gene regulation shapes development and disease, with a focus on childhood cancers such as neuroblastoma and brain cancer. Our work spans transcriptomics, regulatory networks, transcription factors, alternative splicing, microRNAs and circular RNAs. By integrating single-cell and bulk transcriptomic data with functional studies in stem cell differentiation and in vivo models, we uncover how gene regulatory programs drive cancer phenotypes and cell state transitions.
Research themes include:
Our approach is grounded in biology and powered by data.
Working in close partnership with wet-lab collaborators, we design experiments to dissect systems, use computational biology to ask sharper questions, make more insightful predictions, and close the loop as collaborators take these findings back to the bench for validation.