- Genome Center
- MIND Institute
- Department of Biochemistry and Molecular Medicine, School of Medicine
Algorithms for sequence (Genome) analysis
- Computational methods for structural variation discovery and genotyping: Structural variation are understudied type of genetic variation which have a significant effect on human health and evolution. As a lab we are working on developing novel computational methods for discovery of structural variation in whole-genome sequenced samples. We are interested in applying these methods to discover novel structural variation associated with complex disorders (e.g. autism and cancer).
- Genome assembly: We are interested in developing novel algorithms for better de novo genome assembly using different sequencing technologies.
System biology and disease predictions
- Discovery of modules and pathways in complex disorders: One of the main projects in my lab is developing algorithms for discovery of modules and pathways contributing to neurological disorders.
- Prediction of complex disorder using rare and common variants: Finally, we are also interested in developing new classification algorithms which can predict the phenotype (e.g. disease or normal) of samples only based on observed -omics data (e.g. variants, expression, etc).