Shu-Dong Zhang initially trained as a physicist with a PhD from Beijing Normal University, specialising in non-equilibrium statistical physics and non-linear dynamics.
Before embarking on biology-oriented research, he worked on various topics in statistical physics, condensed matter physics and physical chemistry. Inspired and excited by the rapid advancement of modern biotechnologies, especially the high throughput omics technologies and the Human Genome Project, he became interested in quantitative and computational biology.
In 2002, he joined the Medical Research Council (MRC) Toxicology Unit to work side by side with biomedical scientists on transcriptomic profiling, particularly on the experimental design, methodology development, and data analysis issues associated with microarray technologies. He developed a statistical framework for designing two-colour cDNA microarray experiments, and related methods and tools to effectively detect differential gene expression. Dr Zhang investigated the effect of sample pooling in microarray experimentation, and the efficiencies and cost effectiveness of such practice. Those methods and tools have been routinely used by colleagues and collaborators in their experiments and data analysis.
Before joining the Northern Ireland Centre for Stratified Medicine, Dr Zhang worked as a Principal Investigator and a Lecturer in Bioinformatics in the Centre for Cancer Research and Cell Biology (CCRCB) at Queen’s University Belfast. One major theme of his research was to establish novel connections between diseases and various small molecule compounds, utilising high throughput transcriptomic profiling data and employing powerful and advanced Bioinformatics techniques.
He led the BBSRC/MRC/EPSRC co-funded project on gene expression connectivity mapping, to develop innovative algorithms (gene signature perturbation, gene signature progression), new software tools (sscMap, cudaMap, QUADrATiC), and novel applications of connectivity mapping to repurpose FDA-approved drugs for cancers, eg, leukaemia, colorectal cancer, and inflammatory diseases, such as cystic fibrosis.
Dr Zhang's research also led to fruitful collaborations with biologists and cancer epidemiologists, securing joint collaborative projects funded by leading charities like Cancer Research UK. For example, applying the advanced connectivity mapping methods developed to a joint CRUK project, his work directly empowered cancer epidemiology research by providing highly promising candidate medications for population based studies with foreseeable healthcare implications.
Dr Zhang’s research generally involves the development of bioinformatics methods and techniques and their applications in biomedical sciences.
For the past few years, he has devoted a significant amount of efforts identifying prognostic and/or predictive biomarkers for different types of cancers with the aim of stratifying cancer patients into different prognosis/treatment groups.
Here at C-TRIC, Dr Zhang continues to pursue his research interest in developing novel methods for Stratified Medicine in the key disease areas of this Centre, through integrating patient clinical data with high throughput omics data including those based on Next Generation Sequencing technologies. Building upon the experience in stratifying cancer patients, combined with his expertise in disease gene signatures and drug-repurposing, Dr Zhang aims to make significant contributions to developing a comprehensive and integrated approach to stratified medicine.
Lecturer and Tutor for the following modules:
BIO337 Mathematical and Computational Methods 2
BIO535 In Silico Genomic Proteomic & Metabolomic Analyses Methods
BIO541 Biomedical Informatics
BIO124 Genetic inheritance and Omic Technologies
Module Coordinator for BIO337 Mathematical and Computational Methods 2, BSc Hons Stratified Medicine.