Fereydoun Hormozdiari

Research Interests

Algorithms for sequence (Genome) analysis

1. 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).
2. Genome assembly: We are interested in developing novel algorithms for better de novo genome assembly using different sequencing technologies. 

System biology and disease predictions

1. 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.
2. 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).