Research

Our lab primarily focus on implementing the computational genomics techniques to identify the genetic drivers of cancer progression and drug resistance. As we know only ~2% of the genome code for proteins and rest of the genome is called as non-coding. Despite being non-coding, it plays critical regulatory roles in cellular homeostasis. We are interested in investigating the non-coding genome and how the genomic aberrations in non-coding genome can initiate the disease. We rely on in-house and public domain computational techniques to analyse high throughput sequencing data from various platforms i.e. whole genome sequencing (WGS), RNA-seq, ChIP-seq and ATAC-seq. Ultimate goal is to identify diagnostic and prognostic markers from the non-coding genome and take it further into the clinics for precision medicine. Currently, we are focusing on glioblastoma multiform (GBM) and acute myeloid leukemia (AML).

We also work in developing of AI/ML based prediction algorithms and biological databases.