The Computational Biology & Gene Regulation group aims at developing cutting-edge bioinformatics tools with immediate application to real-life biological problems. Our computational biology research program focuses on gene expression regulation and the mechanisms by which it can be disrupted in human diseases such as cancer.
The current main focus of the lab is 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.
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.
Amongst others, our current projects aim at developing new computational methods and tools for (1) improving the prediction of transcription factor binding sites; (2) prioritizing somatic mutations dysregulating the gene regulatory program in cancer cells; (3) understanding the interplay between TF binding and DNA methylation in cancers, (4) characterizing the landscape of active promoters and enhancers in breast cancer; and (5) assessing the transcriptional impact of transition from diploid to aneuploid cells in breast cancer.