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