Our group is interested in producing, integrating and discovering patterns in large multi-omics datasets to extend the understanding of transcriptional and post-transcriptional regulatory mechanisms in human brain disorders, specifically neurodegenerative diseases. Integration of different sequencing data types provides an opportunity to investigate biological pathways at multiple layers like genotype, chromatin and transcript levels. We (together with collaborators) use iPSCs, human tissues and mouse models to generate cell-type specific multi-omics data (like scRNA-seq and scATAC-seq) to better understand diseases related to the brain and nervous system, such as Alzheimer's disease (AD), Frontotemporal dementia (FTD) and Parkinson's disease (PD).

We are also interested in exploring a role of non-coding part of the genome. According to the current human proteome, only ~1% of our genome encode for proteins, which work together to underlie most of the structure and function of our cells and organs. Thus ~99% of our non-coding genome comprises the critical information dictating the regulation of protein-coding genes during our life and development. For instance, more than half of this non-coding DNA is derived from transposable elements (TEs), repetitive DNA segments that are capable of moving and replicating in the genome and has been associated in many human diseases. Notably, along with the gene expression, the activity of these non-coding regions seems to be cell-type specific. Therefore, combining disease-specific mutation information of non-coding DNA regions at cell-type resolution offers a potential to capture genetic complexity, a molecular basis of normal brain function, and a transition to neurological disease.