Research in the group focuses on modeling biological data using networks and applying graph algorithmic and machine learning techniques to mine these data and extract patterns of biological significance. Example projects include:

Inferring subnetworks that underlie a biological process of interest by integrating protein network data with gene expression or phenotypic information (see 1, 2).

Modeling mutational processes in cancer using machine learning techniques (see 1, 2).

Construction and analysis of Boolean network models using machine learning and integer programming techniques (see 1, 2).

Predicting drug properties and their applications in the clinical practice (see 1, 2).