Research Activities
Development of high-throughput CRISPR screening platforms, integrating machine learning-guided library design with large-scale genetic perturbation experiments in different biological contexts
Application of advanced statistical methods, machine learning, deep learning, explainable AI (XAI), and data mining for predicting pathological mechanisms, identifying disease biomarkers and supporting patient stratification.
Development, application and optimization of automated pipelines for the analysis of genomics, epigenomics and transcriptomics data for large-scale studies.
Deployment and application of automated analysis pipelines for the analysis of bulk, single-cell and spatial transcriptomics data.
Characterization of the functional landscape of single nucleotide variants (SNV) in disease models by using large-scale CRISPR screens and quantifying variant effects via phenotypic and transcriptional readouts











