Publications by authors named "Ellora Hui Zhen Chua"

Why biological age is a major risk factor for many of the most important human diseases remains mysterious. We know that as organisms age, stem cell pools are exhausted while senescent cells progressively accumulate. Independently, induction of pluripotency via expression of Yamanaka factors (; OKSM) and clearance of senescent cells have each been shown to ameliorate cellular and physiological aspects of aging, suggesting that both processes are drivers of organismal aging.

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Proper embryonic development requires directional axes to pattern cells into embryonic structures. In Drosophila, spatially discrete expression of transcription factors determines the anterior to posterior organization of the early embryo, while the Toll and TGFβ signalling pathways determine the early dorsal to ventral pattern. Embryonic MAPK/ERK signaling contributes to both anterior to posterior patterning in the terminal regions and to dorsal to ventral patterning during oogenesis and embryonic stages.

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The expression of a large number of genes is regulated by regulatory elements that are located far away from their promoters. Identifying which gene is the target of a specific regulatory element or is affected by a non-coding mutation is often accomplished by assigning these regions to the nearest gene in the genome. However, this heuristic ignores key features of genome organisation and gene regulation; in that the genome is partitioned into regulatory domains, which at some loci directly coincide with the span of topologically associated domains (TADs), and that genes are regulated by enhancers located throughout these regions, even across intervening genes.

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Patients with Alzheimer's disease suffer from a decrease in brain mass and a prevalence of amyloid-β plaques. These plaques are thought to play a role in disease progression, but their exact role is not entirely established. We developed an optogenetic model to induce amyloid-β intracellular oligomerization to model distinct disease etiologies.

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Mutational signatures are characteristic patterns of mutations generated by exogenous mutagens or by endogenous mutational processes. Mutational signatures are important for research into DNA damage and repair, aging, cancer biology, genetic toxicology, and epidemiology. Unsupervised learning can infer mutational signatures from the somatic mutations in large numbers of tumors, and separating correlated signatures is a notable challenge for this task.

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