Multi-omics and multi-layer data integration
Development of computational strategies to integrate data across multiple biological layers (genome, transcriptome, epigenome, proteome) and heterogeneous technologies (short- and long-read sequencing). The goal is to design models capable of harmonizing diverse evidence sources to enhance the accuracy and interpretability of complex genomic data.
Structural variant (SV) refinement and biomedical annotation
Design of a computational framework for the refinement and biomedical annotation of structural variants by integrating multiple omics layers. The approach involves harmonization strategies and ML to capture cross-modal consistency and improve variant classification and interpretation.
Scalable infrastructures for computational genomics
Implementation of modular, containerized, and reproducible pipelines deployable on both cloud and high-performance computing (HPC) environments. These infrastructures aim to support large-scale multi-omics analyses and ensure scalability, interoperability, and reproducibility in biomedical research.
