Breast Cancer Data Science Group
Dr Syed Haider’s multidisciplinary team combines bioinformatics and statistical machine learning techniques to identify therapeutic vulnerabilities and biomarkers of aggressive disease, particularly in breast cancer.
Research, projects and publications in this group
Our group employs a range of data science techniques to prioritise candidate genes by prosecuting multi-modal bulk and single-cell molecular profiles. We also enable bioinformatics research and development in the breast division encompassing both hypothesis-driven and hypothesis-generating translational research.
Dr Syed Haider
Group Leader:
Breast Cancer Data Science Group
Dr Syed Haider’s multidisciplinary team combines bioinformatics and statistical machine learning techniques to identify therapeutic vulnerabilities and biomarkers of aggressive disease, particularly in breast cancer.
Researchers in this group
.
.
Dr Karolina Benkova works on the analysis of single-cell and spatial transcriptomics data across multiple research groups in the Breast Cancer Division. She has a background in applied mathematics, with a PhD in PDE-constrained optimisation in mathematical biology, and experience in developing numerical methods and computational models. Her current work involves developing and applying bioinformatics pipelines for large-scale omics data in cancer research.
Dr Syed Haider's group have written 62 publications
Most recent new publication 11/2025
See all their publications
.png?sfvrsn=110bfd2c_1 "New data tool could bring RNA sequencing into standard clinical practice, improving diagnosis and treatmentArticles Hero Banner (2)")
