Research
Integrative single-cell data analysis
The recent explosion of high-throughput single-cell omics necessitates the development of computational toolkit which can integrate data from multiple sources, cell types and biological layers (e.g. RNA-seq vs ATAC-seq). We aim to develop computational methods and databases which can integrate all publicly available single-cell data into one huge cellular network, leading to the creation of multi-layered single-cell atlas.
Polanski et al. Bioinformatics, 2019
https://github.com/Teichlab/bbknn
Single-cell genomics as new diagnostic tool for complex immune disease
"Our immune system is characterised by diversity, specificity, plasticity, and adaptability—properties that enable them to contribute to homeostasis and respond specifically and dynamically to the many threats encountered by the body. Single-cell technologies are ideally suited to studying these properties of immune cells."
Our research aim to understand immune response at system level and improve the resolution of diagnosis, providing personalised report for immune status. Our final goal is to build single-cell based diagnosis platform for complex immune disease which can be used in daily basis. We are interested in various types of immune-related pathology, such as infection, inflammation, autoimmunity and immune tolerance in cancer.
thymus atlas web portal, codes and data
Efremova, Vento-Tormo, Park et al. 2020. Annual Review of Immunology
Understanding development and ageing from the integrated cell atlas
Single cell genomics provide powerful toolkit to understand development and ageing process. We aim to build and utilise big single-cell atlas to derive common themes and logics across lifetime changes in cell status. We are actively collaborating with developmental biologists to develop new single-cell based techniques which can efficiently link the big-data driven hypothesis with real-world experiments.