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.
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), Science Translational Medicine, 13
The bromodomain inhibitor JQ1+ reduces calcium-sensing receptor activity in pituitary cell-lines.
Lines KE. et al, (2021), J Mol Endocrinol
A blood atlas of COVID-19 defines hallmarks of disease severity and specificity
COvid-19 Multi-omics Blood ATlas (COMBAT) Consortium None. et al, (2021)
Heterogeneous disease-propagating stem cells in juvenile myelomonocytic leukemia.
Louka E. et al, (2021), J Exp Med, 218