Our expertise is in implementing Bioinformatics methods and machine learning models to solve biological research and clinical outcome questions.
Key research areas
Biomedical and health data infrastructure
Biomedical data standardisation and quality control following international data and metadata standards to enable FAIR data life cycle.
Multimodal data integration for personalised medicine
We employ predictive machine learning methods to automatically learn complex features from individual data types and harmonise heterogeneous multimodal information. We emphasise on generalisability and interpretability.
Integrative Genomics
We merge genomics layers made of functional omics, epigenomics and transcriptomics, creating gene regulatory signatures. We focus on non-coding genome regions, including regulatory elements and ncRNAs.
Natural language processing of unstructured data
Natural language processing of unstructured data. We apply NLP methods to process unstructured text and genomic data.
Projects
Discover additional information regarding the projects underway in our lab.
