The two main research directions include:
- Cancer Risk and Biological Age Assessment: development of methods, algorithms, and assay to quantify multi cancer risk based on the accumulation of DNA mutations, integrating multi-omic and clinical data. The work combines theoretical development with data-driven analyses, from pilot studies to population-scale datasets, using approaches such as stochastic processes, latent variable models, stochastic differential equations and statistical methods.
- Early Cancer Detection: design of methods and bioinformatics pipelines to detect early cancer signals by analyzing DNA fragmentation patterns, aneuploidy methylation and mutations in cell-free DNA (cfDNA). This includes developing algorithms to classify samples as healthy or cancerous while accounting for batch effects, applicable to whole-genome sequencing or amplicon-based approaches.
