Research projects

This study explores how dynamic changes in ribosomal DNA (rDNA) chromatin contribute to cancer development, aiming to uncover mechanisms of malignant transformation and potential therapeutic targets.

This project focuses on the role of H2A.B in spermatogenesis under heat stress.

This project focuses on novel morphometric analysis methods for emerging types of 3D image data.

Our research focuses on inhibiting nucleic acid sensing receptors or signaling pathway molecules to prevent autoantibody production and autoimmune pathology in autoimmune mouse models, in collaboration with the Gantier Group at the Hudson Institute of Medical Research.

We investigate cytokine roles in SLE and opportunities for projects studying their impact on autoreactive B cell survival, focusing on identified genetic variants and therapeutic targets.

We investigate how cell-cell communication, adhesion, fluid flow, and microstructure control cell migration and tissue formation in response to dynamic extracellular conditions.

We're developing PDIP, a peptide derived from PF4, to combat malaria by targeting and killing parasites inside infected cells; current efforts focus on optimizing its structure and combining it with existing drugs for enhanced efficacy.

Our goal is to harness extensive single-cell and spatial transcriptome datasets to decipher APA/AS patterns and gene expression simultaneously, expanding the scope beyond conventional single-cell expression analysis.

The aim of this project is to better understand how the bacteria defend against viral infection and how we can take advantage of the bacteria defence system to harness it as a gene editing technology.

This study aims to develop effective combination therapies using RNA Polymerase I (Pol I) inhibitors to enhance therapeutic efficacy and combat resistance in cancer treatment through synergistic effects with other drugs or treatments.

While there is no perfect model to simulate all the pathologies associated with human AMD, we use a growing number of approaches to better understand the progression of AMD and retinal degenerations in general. These models also serve to test the efficacy of novel AMD therapeutic and diagnostic pipelines.

This project advances the development of innovative machine learning models designed to unearth conserved cis-regulatory RNA structures across vertebrate genomes. This initiative includes the creation of new RNA structure 2D/3D modeling and comparative genomics methods, underpinned by robust neural network architectures.

This project focuses on understanding the role of WNT in congenital heart defects.