I have a strong background in Bioinformatics and scripting languages, which underpin my expertise, knowledge, and motivation to carry out data analysis. It has become pivotal for most research projects to have a computational biologist who can work with supercomputers to extract information from the vast genomic data now available and subsequently to analyze it. After finishing my Bachelor’s Degree, I entered a Masters in Bioinformatics program at NYU School of Engineering, Polytechnic University, where I focused my training in Next Generation Sequencing technologies and data manipulation in Perl, Bio Perl, R base, R Bio conductor libraries, and MATLAB. During my Master’s Program, I worked in the Center for Genomics and Systems Biology in Michael Purugganan’s Laboratory to examine and annotate different rice genomes for the MSU rice genome project, using Perl/Bio Perl and R with Nippon Bare rice as a reference genome. I developed bioinformatics pipelines for the rice genomes and dealt with genome assembly, genome annotation, transcriptome analysis, etc.

In 2011, I joined the Albert Einstein College of Medicine as a data analyst with Prof. Jonathan R. Warner to study bioinformatics of ribosome biogenesis. We investigated 80 ribosomal protein genes under different conditions of development and disease, particularly cancers. I used RNA-Seq data from Einstein collaborators and from published datasets to analyze regulation of transcription of ribosomal protein mRNAs. Because of peculiarities of the ribosomal protein genes, the major one being the number of pseudogenes for 80 ribosomal protein genes, I developed a novel bioinformatic pipeline for this analysis (Gupta & Warner, 2014). Recently I have found a 3 nucleotide micro-exon in one of the RP genes whose inclusion is tissue specific.

I worked with Prof. Charles Query in the Department of Cell Biology at Einstein. My research involved studying regulation of snRNA transcription, snRNP biogenesis, and developing bioinformatic pipelines to map snRNA repetitive sequences. Together with a graduate student, Brian Kosmyna, I characterized the functional role of previously unrecognized U2 and U6 snRNA variants to determine ultimately what role these variant snRNAs play in splicing. The variant snRNA sequences are highly repetitive, which presents a computational problem using standard mapping algorithms. I tackled this issue by constructing in-silico snRNA genomes consisting of snRNA-only sequences and developing novel bioinformatic pipelines for further down-stream processing steps.

I provide assistance to several laboratories within Cell Biology Department as well as within Einstein for data analysis of RNA-Seq, DNA-Seq, ChIP-Seq etc. and other computational analysis required as per the project.

Currently, I am working under Prof. Marina Konopleva in the Department of Oncology. I am involved in analyzing Clonal hematopoiesis (CH) data using statistical tools like fisher exact test and logistic regression models.

Chen, H., Lorton, B., Gupta, V., & Shechter, D. (2017). A TGFβ-PRMT5-MEP50 axis regulates cancer cell invasion through histone H3 and H4 arginine methylation coupled transcriptional activation and repression. Oncogene 36:373-386, PMID27270440; PMC5140780; doi:10.1038/onc.2016.205.

Gupta, V., Moldón, A, Xu, Y.-Z., and Query, C.C. (2016).  SF3B1/Hsh155 HEAT motif mutations affect interaction with the spliceosomal ATPase Prp5, resulting in altered branch site selectivity in pre-mRNA splicing. Genes & Dev. 30, 2710–2723.  PMID28087715; PMC5238730; doi:10.1101/gad.291872.116.

A De La Garza, RC Cameron, V Gupta, E Fraint, S Nik, TV Bowman(2019). The splicing factor Sf3b1 regulates erythroid maturation and proliferation via TGFβ-PRMTsignaling in zebrafish. Blood Adv. 2019 Jul 23;3(14):2093-2104. PMID:31300417 ; doi: 10.1182/bloodadvances.2018027714.

*These authors contributed equally to this work.