📍 Kolkata, West Bengal, India
💼 Open to relocation & Full-time positions

I am a passionate Life Sciences postgraduate bridging the gap between wet-lab experimental research and dry-lab computational workflows. With a foundational background in Botany (M.Sc.), my expertise spans interdisciplinary experimental research under GLP standards, nanomaterial biosynthesis, microbial assays, and NGS/RNA-Seq data analysis. I specialize in integrating laboratory findings with data-driven computational interpretation to support translational and genomics-focused research outcomes.

🔬 Research Interests: Drug development from Biosynthesized Nanoparticles, Translational Genomics, Next-Generation Sequencing (NGS), RNA-Seq Data Analysis, and Computer-Aided Drug Design (CADD)

• Sequence Alignment: BLAST, ClustalW, Clustal Omega, MUSCLE
• NGS Workflow: SRA Toolkit, FastQC, Trimmomatic, Cutadapt, BWA, Bowtie2, SAMtools, GATK
• RNA-Seq & DEG Analysis: STAR, DESeq2, edgeR
• Visualization & Structural Modeling: PyMOL, RasMOL, Chimera, SWISS-MODEL, I-TASSER, AlphaFold, SwissDock, diffDock
• Databases: NCBI, Ensembl, PDB, UniProt, Expasy

• Languages: RStudio (GEOquery, DESeq2, ashr, ggplot2, pheatmap), Python (Pandas, NumPy, Matplotlib, Seaborn)
• Development Environments & Platforms: Linux/Bash (Basic), Galaxy Platform, Visual Studio Code, Google Colab, Kaggle
• Data Visualization: Power BI, Tableau, MS Excel

• Sterile & Aseptic Techniques, Sample Preparation & Analysis, Microbial Culture Maintenance, Light microscopy and computer-assisted biological sample visualization, Morphological assessment & strain verification
• Nanoparticle Biosynthesis, UV-Visible Spectroscopy, Antibacterial & Bioassay Techniques
• Interdisciplinary Research, Experiment Designing, Scientific Writing & Documentation, SOP Compliance, GLP Practices

• Built an end-to-end tumour-only somatic variant-calling pipeline for triple-negative breast cancer whole-exome data (2026 TNBC cohort, PRJNA1422845), implementing the full GATK Best Practices workflow: BWA-MEM alignment, duplicate marking, Base Quality Score Recalibration, and Mutect2 tumour-only calling with a gnomAD germline resource, Panel of Normals, and orientation-bias/contamination modelling.
• Engineered the analysis for reproducibility and efficiency by subsetting the GRCh38 reference to chromosomes 13 and 17 (BRCA2, BRCA1, TP53), and annotating variants locally with snpEff, then prioritising against a hereditary breast-cancer gene panel using a gnomAD rarity filter to compensate for the absence of a matched normal.
• Identified candidate somatic loss-of-function mutations in TP53 in 2 of 3 tumours — a nonsense (p.Glu310*) and a frameshift (p.Gly69fs) variant, both HIGH-impact and absent from gnomAD — consistent with TP53's role as the dominant, characteristically truncating driver in TNBC, validating the pipeline against known disease biology.
• Documented the workflow as a reproducible, well-annotated Jupyter notebook with integrated QC (FastQC/MultiQC), explicit handling of the tumour-only design's limitations, and transparent reporting of candidate variants and per-sample results.

• Conducted a full RNA-seq differential gene expression analysis on the GSE147507 dataset, comparing SARS-CoV-2 infected vs mock-treated samples across four respiratory cell lines — NHBE, A549, A549-ACE2, and Calu3, using DESeq2 in RStudio with fold-change shrinkage for more reliable results.
• Quality control visualisations, including PCA, sample distance heatmaps, and dispersion plots, confirmed that replicates were consistent, cell lines separated cleanly, and the statistical model fitted the data well before any differential testing was performed.
• SARS-CoV-2 infection produced strikingly different outcomes across different cell lines. NHBE showed broad gene suppression (22 of 25 significant genes were switched off), while A549-ACE2 produced 658 differentially expressed genes, nearly 30 times more than the ACE2-low A549 parent line, highlighting how critical receptor availability is to the scale of the host response.
• These patterns were consistently reflected across volcano plots, MA plots, and expression heatmaps, which together showed sparse and suppressive responses in primary airway cells versus large, predominantly activating responses in the ACE2-expressing models.

• Optimized a fibroblast-to-sensory-neuron differentiation protocol.
• Built Generalized Linear Models (binomial logistic regression) in RStudio to evaluate treatment effects and categorical factor encoding. Conducted robustness and outlier reanalysis.
• Analyzed immunocytochemistry (MAP2, TRKA) and functional $Ca^{2+}$ imaging datasets for nociceptor specification and functional maturation.

• Objective: Conducted client telemetry and HR telemetry data investigations.
• Tech Stack: Excel, Tableau
• Impact: Cleaned and transformed large datasets to investigate indicators of corporate unfair pay practices and built interactive dashboards for key performance metrics.

• Objective: Green synthesis of silver nanoparticles (AgNPs) from 8 cyanobacterial strains and evaluating antibacterial potential.
• Methodology: Optimized culture conditions in BG-11 media, validated synthesis of AgNPs via UV-Vis spectrophotometry peaks (429–460 nm), and ran microtiter plate assays against multidrug-resistant pathogens.

• Bioinformatics Summer Research Internship | BioTecNika (Public Databases, Global Bioinformatics Tools, CADD, ADMET Profiling)
• Next-Gen Sequencing & Multi-Omics Data Analysis Internship | BioTecNika (Linux for Bioinformatics, NGS Workflow, RNA-Seq & DEG Analysis, Multi-Omics Integration)
• Immunogenomics Certificate Course | BioTecNika (HLA Genetics & Transplant Immunology, Cancer Immunogenomics, Translational Genomics & Therapeutic Frameworks)

• ✉️ Email: ghoshparnabali@gmail.com
• 💼 LinkedIn: https://in.linkedin.com/in/parnabali-ghosh-295091114