Computational BioMedicine Laboratory
Using machine learning, mathematical modelling, and molecular dynamics simulations we investigate mechanisms of post-transcriptional gene regulation. We found, for example, that synergistic target regulation by microRNAs is a widespread phenomenon of post-transcriptional gene regulation – a mechanisms that can be exploited to sensitize aggressive tumour cells to chemotherapy.
We develop multi-omics data analysis pipelines to investigate patterns of alternative splicing and other forms of gene regulation in normal biology and in various cancers. We identified intron retention as a well conserved form of alternative splicing that mediates cell-specific gene regulation. Aberrant intron retention has been described in multiple human cancers. We aim to identify regulators and consequences of intron retention as well as cross-talk with other forms of post-transcriptional gene regulation.
Using machine learning, mathematical modelling, and molecular dynamics simulations we investigate mechanisms of post-transcriptional gene regulation. We found, for example, that synergistic target regulation by microRNAs is a widespread phenomenon of post-transcriptional gene regulation – a mechanisms that can be exploited to sensitize aggressive tumour cells to chemotherapy.
We develop multi-omics data analysis pipelines to investigate patterns of alternative splicing and other forms of gene regulation in normal biology and in various cancers. We identified intron retention as a well conserved form of alternative splicing that mediates cell-specific gene regulation. Aberrant intron retention has been described in multiple human cancers. We aim to identify regulators and consequences of intron retention as well as cross-talk with other forms of post-transcriptional gene regulation.
