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.
Processing single-cell RNA-seq datasets using SingCellaR.
Wang G. et al, (2022), STAR Protoc, 3
CD34+CD19-CD22+ B-cell progenitors might underlie phenotypic escape in patients treated with CD19-directed therapies.
Bueno C. et al, (2022), Blood
Ezh2 is essential for the generation of functional yolk sac derived erythro-myeloid progenitors.
Neo WH. et al, (2021), Nat Commun, 12
Transitions in lineage specification and gene regulatory networks in hematopoietic stem/progenitor cells over human development.
Roy A. et al, (2021), Cell Rep, 36
Single-cell profiling of human bone marrow progenitors reveals mechanisms of failing erythropoiesis in Diamond-Blackfan anemia.
Iskander D. et al, (2021), Sci Transl Med, 13