Turning biological data into scalable insights
What if DNA isn’t just biology,but nature’s most elegant technology?
That idea is what pulled me into bioinformatics. I’m fascinated by how information is encoded, regulated, and expressed within living systems and how we can read, model, and even redesign those processes using computation. With a background in genetic engineering, I’ve spent time both at the bench and behind the screen, understanding how biological data is generated and how it can be interpreted at scale. I work at the intersection of biology and computation to explore patterns in biological data and to build end to end systems that make those patterns easier to understand and use. What excites me most is the possibility of treating biology not just as something to observe, but as something to engineer, optimize, and translate into real world impact whether that’s in health, research, or emerging biotechnologies.
Snakemake • assembly validation • synteny analysis • annotation error detection (mChlEAn)
Optimized pipeline using ML • Flask API • Angular frontend
View Analysis Report →Workflow design • PLS-DA • biomarker discovery • ML models (KNN, SVM, Random Forest)
View Analysis Report →VCF/BCF parsing & variant extraction using BCFtools and Picard
View Analysis Report →End-to-end RNA-seq: QC • alignment • differential expression • SNP/INDEL calling • HPC
View Analysis Report →De novo • hybrid (DBG2OLC, MaSuRCA, HybridSPAdes) • long-read (Canu, FALCON) • short-read (SOAPdenovo2, Velvet, IDBA) • k-mer analysis
View Analysis →QIIME2 • DADA2 denoising • phylogenetic & taxonomic analysis in R
View Analysis Report →Java • FASTA/GTF parsing • exon visualization • sequence stats
View Analysis Report →VCF parser • SQLite • REST API • variant querying • density analysis
AutoDock & PyRx docking • ADME profiling
Molecular Techniques (I & II), Immunology Lab, Microbial Genetics Lab, Cytogenetics Lab, Recombinant DNA Technology, Enzyme Engineering, Gene Expression, Animal Cell Culture, Plant Genetic Engineering, Bioseparation Engineering
Data Domains:
Genomics, Transcriptomics, Proteomics, Metabolomics, Epigenetics, Metagenomics, NGS
Tech Stack:
Python, R, Java, SQL (SQLite), Bash, Machine Learning, REST APIs, Node.js, Express.js, JavaScript
Unilever • England, UK
GA-based optimization • ML modeling • Flask REST API • Angular frontend • end-to-end pipeline
Chennai • India
Pedigree analysis • mutation visualization • genomic data interpretation • ethical data handling
Remote
Top 15% educator • mentoring • communication • student engagement
SRM university
Committee Head & Event Coordinator • team leadership • DNA workshop (300+) • microscopy challenge • outreach impact
SRM university
Awareness campaigns • community outreach • event coordination
Bentham Science Publishers • 2020
View Publication →dnalabz@arpanpardeshi.com
arpan.pardeshi1999@gmail.com
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