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).
Grad Group Affiliations
- Computer Science
- Integrative Genetics and Genomics
- 2004 B.Sc. Computer Engineering Sharif University of Technology
- 2007 M.Sc. Computing Science Simon Fraser University
- 2011 Ph.D. Computing Science Simon Fraser University
F. Hormozdiari, O. Penn, E. Borestein, EE. Eichler
The discovery of integrated gene networks for autism and related disorders.
Genome Research 2015
M. Chaisson, J. Huddleston, MY. Dennis, PH. Sudmant, M. Malig, F. Hormozdiari, et al.
Resolving the complexity of the human genome using single-molecule sequencing.
F. Hormozdiari, MK. Konkel, J. Pardo-Martinez, G. Chiatante, IH. Herraez, et al.
Rate and Patterns of great ape retrotransposition.
Proc. Natl. Acad. Sci. (PNAS) 2013
The 1000 genome Project Consortium.
A integrated map of genetic variation from 1,092 human genomes.
F. Hormozdiari, I. Hajirasouliha, A. McPherson, EE. Eichler, SC. Sahinalp
Simultaneous structural variation discovery in multiple paired-end sequenced genomes.
Genome Research 2011
F. Hormozdiari , C. Alkan, M. Ventura, I. Hajirasouliha, et al.
Alu repeat discovery and characterization within human genomes
Genome Research 2011
A. McPherson, F. Hormozdiari, A. Zayed, et al.
deFuse: An Algorithm for Gene Fusion Discovery in Tumor RNA-Seq Data.
PLoS Computational Biology 2011
RE. Mills, et al.
Mapping copy number variation at fine-scale by population-scale genome sequencing.
F. Hormozdiari, I. Hajirasouliha, P. Dao, F. Hach, D. Yorukoglu, C. Alkan, EE. Eichler, SC. Sahinalp
Next Generation VariationHunter: Combinatorial Algorithms for Transposon Insertion Discovery.
F. Hormozdiari, R. Salari, V. Bafna, SC. Sahinalp.
Protein-protein interaction network evolution for identifying potential drug targets.
Journal of Computational Biology 2010
I. Hajirasouliha, F. Hormozdiari, C. Alkan, JM. Kidd, I. Birol, EE. Eichler, SC. Sahinalp
Detection of locus and content of novel sequence insertion using paired-end next-generation sequencing.
F. Hach, F. Hormozdiari, C. Alkan, F. Hormozdiari, I. Birol, EE. Eichler, SC. Sahinalp.
mrsFAST: a cache-oblivious algorithm for short-read mapping.
Nature Methods 2010
The 1000 Genome Project Consortium.
A map of human genome variation from population-scale sequencing
F. Hormozdiari, C. Alkan, EE. Eichler, SC. Sahinalp.
Combinatorial Algorithms for Structural Variation Detection in High Throughput Sequenced Genomes.
Genome Research 2009
I. Hajirasouliha, F. Hormozdiari, SC. Sahinalp, I. Birol.
Optimal pooling for genome resequencing with ultra-high throughput short read technologies.
F. Hormozdiari, P. Berenbrink, N. Przulj, SC. Sahinalp
Not all scale-free networks are born equal: the role of the seed graph in PPI network evolution.
PLoS computational Biology 2007