Research Projects
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Developing innovative FFPE-CUTAC methodology for mapping RNA Polymerase II occupancy in clinical cancer samples, revealing how elevated transcription patterns correlate with cancer progression and prognosis.
Developing a novel normalization and integration method for antibody-derived tags (ADTs) in CITE-seq data, enabling accurate alignment of protein expression across batches and facilitating atlas-level analyses of single-cell multimodal data.
Developing advanced statistical methods and computational tools for analyzing 3D genome structure data, with applications in understanding gene regulation mechanisms and disease-associated genetic variants.
Utilising advanced AI to process multimodal cardiothoracic data for enhanced diagnosis and prognosis of Cardiothoracic Disease (CTD), paving the way for personalised medical care and transformative approaches in heart and lung health.
Developing computational methods for integrating single-cell multi-omics data, including 3D chromatin structure (scHi-C), transcriptomics (scRNA-seq), and proteomics (CITE-seq) data, to better understand cellular heterogeneity and gene regulation.