Research

Computational Genomics

In the realm of computational genomics, my research encompasses diverse domains:

A) Human Microbiome Research: I deeply explore the human microbiome using a combination of 16S metagenomics and shotgun sequencing techniques, enriched with computational systems biology to dissect intricate host-pathogen interactions. I possess expertise in the comprehensive analysis of data generated from state-of-the-art next-generation sequencing platforms like Hiseq, Miseq, and Illumina. My research within this domain spans from investigating bacterial taxonomical diversity to conducting a wide range of studies, including Genome-wide Association Studies (GWAS), Phenome-wide Association Studies (Phewas), Gene Set Enrichment Analysis, Complex Trait Mapping, Bulk-scale RNA sequencing, microRNA analysis, and Single-cell RNA sequencing. To navigate this diverse landscape, I employ advanced tools like Seurat, UMAP, and PHATE..

B) Gene Ontology Pathway & Network Analysis: Specializing in gene ontology, I am well-versed in pathway identification and network analysis. I leverage resources like KEGG, Geo-Ontology, Blast2GO, WEBMGA, Cytoscape, Bingo, and Ingenuity Pathways Studio to gain insights into the functional relationships within the genetic landscape.

C) Microbial Genomics: My expertise extends to the domain of microbial genomics, where I engage in genome assembly, both de novo and reference based. I utilize Kmer Centroid and De Bruijn algorithms to unravel the genetic intricacies of microorganisms. Additionally, I conduct gene ontology analyses to decipher the functional aspects of microbial genomes.

D) Metabolomics and Transcriptomics: I bring my expertise to the field of microbial genomics, where I specialize in genome assembly, encompassing both de novo and reference-based approaches. I apply K-mer Centroid and De Bruijn algorithms to unravel the genetic complexities of microorganisms. Furthermore, I perform gene ontology analyses to unveil the functional attributes embedded within microbial genomes.