Dr Shi develops computational methods for analyzing high-throughput molecular data including next-gen sequencing data and microarray data. (Bioinformatics, computational biology, computer science, genomics, gene expression, next-generation sequencing, microarray)
NGS technologies provide single-nucleotide resolution in measuring molecular changes in cells, and they have fundamentally transformed medical research. However, a significant challenge for analysis of NGS data lies in the processing of massive volumes of read data.
We develop highly efficient and accurate algorithms for the analysis of NGS data, and these algorithms are implemented in easy-to-use software programs that have been used worldwide.
The methods we develop include:
- ‘Seed-and-vote’ read mapping for short and long NGS reads. - Detection of structural variants and complex indels in normal and cancer genomes. - Quantification of expression levels of genes, transcripts and exons.
Another arm of research in my lab is to use a genomic approach to investigate the differentiation of lymphocytes in our immune system. We collaborate with world-leading immunologists to profile global changes of gene expression during lymphocyte differentiation, and we aim to discover novel target genes for improved vaccine design and therapy.
My lab works on developing computational methods for biological investigations. We develop high-performance and practical software tools for analysing high-throughput molecular data such as next-generation sequencing (NGS).
We employ genomic approaches to study molecular mechanisms regulating immune responses of our body to antigen infections. We are particularly interested in investigating the differentiation of lymphocytes, including B cells, regulatory T cells (Treg), nature killer (NK) cells and innate lymphoid cells (ILC), upon infection.
We are also interested in developing accurate and efficient tools for discovering genes and mutations implicated in immune disorders and cancers.