Our research primarily focuses on developing novel statistical and combinatorial algorithms to analyse massive genomic datasets and provide biological insights. A defining aspect of our computational genomics work is the use of parametric complexity analysis (Nagarajan & Pop, JCB 2009) and exact algorithms (Gao et al., RECOMB, JCB 2011; Wilm et al., NAR 2012) to design bioinformatics tools with provable performance guarantees. We primarily focus on addressing questions in three areas a) Sequence Analysis & Assembly
b) Metagenomic Analysis
and c) Integrative Genomics
The genomics tools developed in the group cater to two broad application areas where we work with clinicians and domain experts to address opportune biological and clinical questions impacting human health:
A) Human Microbiome Studies
We develop analytical approaches that leverage advances in sequencing technologies (e.g. PacBio, Nanopore) to decipher the functional role of microbial communities resident in the human body. These are then combined within a systems biology framework to understand how host-microbiome interactions influence health and disease states. Our goal is to identify novel biomarkers and therapeutic targets to help restore microbial symbiosis. Areas of current work in the lab include (i) Role of skin microbiota in Atopic Dermatitis
(w/ Dr. John Common) ii) Impact of antibiotic therapy on gut microbiome
(w/ Dr. Barnaby Young) and iii) Microbial dysbiosis in cholangiocarcinoma
(w/ Dr. Joanne Ngeow).
B) Personalized & Integrative Cancer Omics
We are designing systems to integrate diverse cancer omics datasets to identify driver mutations and effective drug combinations (w/ Dr. Iain Tan and Dr. Ramanuj Dasgupta). The goal is to make molecular profiling data useful for targeted and personalized therapy.