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Ouyang Fengcong John

Principal Research Scientist, Centre for Computational Biology

Duke-NUS Medical School

Bio

I transitioned from a computational chemistry background into bioinformatics when I started my first post-doctoral stint in Duke-NUS Medical School. Since then, I have taken an interest in understanding the molecular drivers underpinning cell fate transitions in various context such as cell reprogramming and cancer progression. In particular, the emergence of single-cell transcriptomics (scRNA-seq) has allowed us to study these cell fate transitions at an unprecedented resolution. Furthermore, the large volume of data generated from such omics approach is highly amenable to machine / deep learning frameworks.

My research interest focuses on the development of machine / deep learning-based computational tools to uncover clinically meaningful biological insights from complex single-cell omics data. Applications of the tools include (i) the identification of biomarkers to stratify patient groups, (ii) perturbation modelling to identify TFs or drugs that can reverse dysregulated programs and (iii) system-level descriptions of biological samples. The tools developed by my group are largely agnostic of the underlying biology. However, I enjoy tackling biological questions related to (i) stem cell biology where cell fate is shown to be highly plastic and cells can be reprogrammed into other lineages by manipulating a small number of regulator genes, (ii) modeling of neurodegenerative disorders and brain development and using stem cell-based neural models and (iii) understanding cell fate transitions in hematological malignancies where genetic mutations and microenvironment often lead to cell fate biases.

I am a firm believer that both experimental and computational expertise are required to solve increasingly complex biological problems. Thus, I enjoy collaborating with wetlab co-workers who generate large volumes of next-generation sequencing data to enable data-driven research. My computational expertise has facilitated the interpretation of such large-scale datasets, enabling the generation of hypotheses that can be readily tested experimentally, resulting in high-impact studies. Furthermore, by working with wetlab co-workers, I can better understand the unmet needs in the field, allowing me to develop more tailored computational tools.

My personal website is at https://jfouyang.github.io/.


Education

Doctor of Philosophy

National University of Singapore, Singapore

Bachelor of Science (Chemistry) Hons Class 1

National University of Singapore, Singapore

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