While useful methods exist for the prediction of functional variants within protein encoding exons (covering only 2% of the human genome), the prediction of cis-regulatory variants (CRVs) remains an ongoing challenge. Inherent to delineating CRVs is the need to improve transcription factor binding site (TFBS) and transcription factor (TF) target predictions. These predictions in combination with whole genome sequencing and expression data in cancer samples will enable us to predict the CRVs dysregulating miRNA  and protein coding gene transcription and contributing to carcinogenesis. In the Computational Biology & Gene Regulation group, we plan to develop new methods and tools for

  1. improving TFBS predictions,
  2. predicting functional TFBSs associated to miRNA regulation, and
  3. prioritizing cis-regulatory variants dysregulating miRNAs in cancers.
Cis-regulatory mutation dysregulating the transcription of a miRNA gene.

Our goal is the creation of the next generation of algorithms and software to study miRNA regulation at a genome-wide scale with a direct application to the analysis of miRNA transcriptional dysregulation in cancers.