Disease Mechanisms, Therapeutics, Diagnostics, Omics, Algorithms, Data Analysis
The majority of genetic mutations responsible for common diseases reside within gene-regulatory sequences such as enhancers, promoters and insulators. In addition, transcriptional and epigenetic dysregulation are known to drive tumorigenesis, tumor progression and drug resistance. Thus, gene regulation lies at the heart of disease mechanisms and treatment response.
The Prabhakar Lab uses a combination of high-throughput omics assays (wet-lab) and data analytics (dry-lab) to study gene-regulatory mechanisms of human diseases. In particular, we use single-cell RNA-seq, cohort-scale histone ChIP-seq and other NGS technologies to understand autism, psychiatric drug response, lung and colon cancer, chronic myeloid leukemia, autoimmune disorders and host response to infection.
We also develop cutting-edge algorithms and pipelines
for deriving biological insights from large datasets. This involves statistics, machine learning and extensive benchmarking for performance and scalability.
In addition to curiosity-driven science, we pursue inventions and discoveries that will (hopefully) make a difference in the world. For example, we are engaged in team science to discover markers of immunotherapy response and develop new imaging-based diagnostic technologies. The methods we develop have spawned research collaborations with multiple industry partners spanning biotech, IT and pharma.
Major achievements include the first single-cell transcriptomic analysis of colorectal tumors (Li, Courtois et al., Nat Genet 2017
), the first study of histone acetylation changes in autism spectrum disorder (Sun, Poschmann et al., Cell 2016
), the first large-scale study of variants that alter histone acetylation and contribute to disease susceptibility (del Rosario, Poschmann et al., Nat Methods 2015
) and the first unified signal-processing method for peak detection in whole-genome profiling data (Kumar et al., Nat Biotechnol 2013
). We have also uncovered fundamental properties of transcription factor binding to genomic DNA (Jankowski et al., Genome Res 2013
) and demonstrated that H2BK20ac is a distinctive signature of enhancers and cell-type-specific promoters (Kumar, Rayan, Muratani et al., Genome Res 2016
). Earlier work explored the contribution of gene regulatory elements to human origins (Prabhakar, Noonan et al., Science 2006
; Prabhakar et al., Science 2008
Centre for Big Data and Integrative Genomics (c-BIG)
Autism paper video (Straits Times)
Citations: Google Scholar
Wet-lab PhD students, Postdoctoral Fellows
Computational Biology PhD students, Postdoctoral Fellows 1
Computational Biology PhD students, Postdoctoral Fellows 2