● Led the design of experiments and statistical analysis of high-throughput genomics data for various human complex disorders● Primary research interest lies in leveraging the potential of sequencing the transcriptome (RNA-Seq) of brain tissues to identify genes associated with autism● Managed library construction to data processing and analysis to identify genome-wide differentially expressed genes, isoforms and pathways associated with autism● An essential extension of transcriptome analysis of autism brains is obtaining single base resolution methylation data (bisulfite sequencing) on the age matched brain samples to search for disease-causing epigenetic and transcriptome alterations● In parallel, I am involved in a project to develop biomarkers that can predict who is at high risk for developing sudden cardiac death utilizing the first sudden cardiac death tissue microarrays ever generated● Supervise, train and mentor technical staff

● Primary focus was on the identification of gene relationships, network creation, and epistatic interactions on a systems level for genotype and gene expression datasets● Utilized alternative gene or region definitions that expanded to include genetic variation in the whole-genome rather than only within genes● Apart from gene-based analysis, additionally, worked on pathway-based enrichment of association to complex disorders utilizing high throughput GWAS data

My thesis focused on identification, description and Boolean simulation of potentially relevant biochemical pathways that sufficiently relate to schizophrenia disease etiology.