My overall objective is to work with health care industry to benefit general public. I have experience in data analysis, designing pipelines and statistical inference of complex data. I am familiar with SLURM workload manager, LINUX, High Performance Computing (HPC) and cloud computing. Expert in performing integrative analysis of multi-layered biological datasets and advanced visualization.

Currently, my postdoctoral work focuses on evaluating somatic mutation loads on various differentiated progenitor cells using single-cell approach.

My Ph.D. work was focused on investigating long non-coding RNAs to unfold their molecular mechanism by analyzing different high-throughput sequencing datasets. During my doctoral research work, I gained experience in analyzing datasets from different cell lines and tissues from cancer patients.

★ Analyzed transcriptome and chromatin-based datasets from cell lines and tumors

★ Handled larger datasets from The Cancer Genome Atlas (TCGA), GTEx, ENCODE and dbGAP

★ Performed integrative approaches by combining different datasets such as

• Methylation-based (Methyl-seq, RRBS-seq, MBD-seq-seq, MEDIP-seq)
• RNA-based (RNA-seq, Microarray)
• Protein-based (Proteome array)
• Chromatin-based (ChIP-seq, ChRIP-seq, ChOP-seq)
• Sequence-based (Motif analysis, promoter-proximity analysis, conservation analysis)

★ Designing computational tools to address problems in functional genomics (GeneSCF). https://github.com/genescf

For more information visit https://decodebiology.org