Ran Zhang

Google Scholar, ORCID

I am a UW Data Science postdoctoral fellow with Dr. William Noble at the University of Washington. Before this, I did my undergraduate studies at Tsinghua University, and my graduate studies at Princeton University, supervised by Dr. Olga Troyanskaya.

I am interested in developing machine learning methods to tackle biology-related problems. I started as a wet-lab biologist in undergrad, where I used a combination of experimental approaches – including imaging, biochemistry, cell biology – to study autophagy in human cell lines and yeast. My graduate work is focused on integrating large-scale functional genomics datasets and applying network-based approaches to predict context-specific disease genes and pathways in neurodevelopmental and neurodegenerative diseases and disorders. During my postdoc studies, I develop deep learning methods to integrate and translate single-cell multi-omics profiles across data modality, time and species, to generate biological hypothesis in biological contexts or data modalities where experimental measurement is scarse.

My research interests include:

• Single-cell cross-modality translation to predict cellular profiles in missing data modalities
• Cross-species imputation to transfer knowledge from model organisms to human
• Reprioritization of disease genes using context-specific gene-gene relationship networks
• Data integration across modalities, biological contexts, time, and species