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Supat Thongjuea


Oxford-BMS Research Fellow

I am a computational biologist. I develop and apply computational approaches to analyse large-scale sequencing data generated by single-cell multi-omics technologies to understand normal and malignant cells in hematopoiesis.

I focus on the single-cell transcriptome and epigenome analyses produced by different single-cell platforms (e.g., Target-Seq, 10x genomics) for studying the complexity of hematopoietic stem and progenitor cell subpopulations. I aim to apply single-cell multi-omics combining with a novel development of computational and statistical methods, including machine learning approaches to translational medicine challenges.

My current work focuses on integrating multiple single-cell RNA and ATAC genomics datasets from Acute Myeloid Leukemia (AML) patients undergoing clinical trials. Integrative single-cell multi-omics datasets could help identify distinct cellular compartments and resolve tumour heterogeneity, providing insights into deregulated pathways, transcriptional and epigenetic signatures. This could potentially lead to the discovery of new targets and therapies to address the unmet medical need of AML patients.