Yibi Chen

I am a computational biologist and postdoctoral researcher at the Institute for Molecular Bioscience, specialising in computational oncology and spatial biology. My research focuses on integrating complementary molecular and spatial data modalities to investigate the biological mechanisms underlying breast cancer progression and metastasis.

Drawing on a strong foundation in evolutionary genomics, I study cellular diversity, tumour evolution, and interactions within the tumour microenvironment. I develop computational workflows in R and Python to process, integrate, and interpret spatial transcriptomics, single-cell RNA sequencing, spatial metabolomics, and other high-dimensional datasets.

My current research interests include:

Multimodal Data Integration: Integrating spatial, transcriptomic, genomic, and metabolomic data to generate a more comprehensive understanding of tumour biology.

Tumour Heterogeneity and Microenvironment: Characterising cancer cell states and their interactions with surrounding immune and stromal populations across spatial and molecular contexts.

Biomarker and Therapeutic Discovery: Identifying molecular features, cellular communities, and spatial patterns associated with disease progression, metastasis, and treatment response.

Tumour Evolution: Reconstructing the evolutionary and developmental trajectories of cancer cell populations to understand metastatic dissemination and local tissue invasion.

By combining multimodal data science, spatial biology, and high-performance computing, my work aims to transform complex biological datasets into meaningful insights that support biomarker discovery and precision oncology.