I have worked in the field of next-gen sequencing techniques and developed analytical approaches for 12+ years. My areas of expertise include bioinformatics analysis and tool development, application scalable analytical methods, using high-throughput computing architecture and application development. As a Lead Bioinformatics Software Engineer at the Institute for Genome Sciences, I lead and mentor a team of software engineers responsible for custom bioinformatics analyses and new tool development for genome analysis involving detection of genomic variants, transcriptome analysis involving differential gene expression, differential expression of splices variants, and epigenetic regulation of gene expression. Some of the projects I have contributed to in the past few years include microarray analysis, metagenome analysis, transcriptome analysis, epigenetic analysis, sequence variation, and next-gen sequence analyses including whole genome sequencing, mRNAseq, ChIPseq, miRNAseq, BSseq, FAIREseq, and ATACseq. I have also utilized my computational skills in the field of population genetics and genome-wide association studies. This work has led to a number of publications in multiple seminal peer-reviewed journals.

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Over the span of 12 years, I have been exposed to a number of projects involving the study of transcriptomic profiles of not only human but also non-human pathogenic datasets including bacterial and fungal infections. These datasets have required the analyses of the differential expression of genes between different pathogen infected and uninfected conditions. Through these projects, I have lead and conducted research to understand how epigenomic perturbations have influenced the expresssion of genes associated with different human phenotypes. I have also conducted research to correlate the differences between multi-omic assays involving a combination of genome, transcriptome, translatome, proteome, and metabolome profiles. I have worked on a number of projects involving cancer datasets investigating the differential expression of protein-coding genes and their isoforms, non-coding RNAs (miRNAs, lincRNAs, piRNAs), sequence variations (SNPs, insertions and deletions) between tumor and normal samples and epigenetic regulations involved in various types of cancers in order to identify both known and novel candidates showing differential expression and associated with cancer-related pathways. I have worked on a number of projects involving population genomics to understand the challenges and disparities in the application of personalized genomic medicine to populations consisting of diverse ancestral background, many of which have been understudied and underrepresented in disease oriented databases. To characterize the extent and impact of population structure in precision genomic medicine, I have worked on a variety of projects involving cohorts representing African populations, Peruvian populations and even non-human malarial populations in order to decipher the fine structure within these populations and shed some light on the impact of population fine-structure and the advantages of incorporating these fine structure estimates to genomic studies.