MSc Bioinformatics (Teesside University, 2025) with 3+ years of clinical laboratory experience spanning molecular diagnostics, antimicrobial resistance research, and microbiome analysis. I build automated pipelines for bacterial genomics and NGS data processing, and I understand the wet-lab context behind the data — having generated a significant portion of it myself.

My work sits at the intersection of computational genomics and applied microbiology: building reproducible workflows, interrogating large-scale genomic datasets, and translating findings into outputs that mean something for AMR surveillance and clinical diagnostics.

Open to opportunities in bioinformatics analysis, NGS pipeline development, and genomics research roles across the UK. Get in touch.

Production-ready Snakemake workflow for large-scale bacterial defence system analysis

Acinetobacter baumannii is one of the WHO's priority pathogens — notorious for acquiring resistance and evading clinical interventions — but the relationship between its phage defence systems and antibiotic resistance gene carriage was poorly characterised. I built an end-to-end automated pipeline to investigate this at scale.

What it does: Retrieves genomes from NCBI, runs DefenseFinder and PADLOC for defence system prediction, ResFinder for resistance gene identification, and integrative mobile element (IME) prediction — then outputs structured result tables ready for statistical analysis. Fully reproducible across fresh environments.

Stack: Snakemake · Python · Bash · DefenseFinder · PADLOC · ResFinder · CRISPRCasFinder

Scale: Validated across 500+ Acinetobacter genomes

R-based statistical analysis of defence system architecture and AMR correlations

Companion repository to the pipeline above. Takes the structured output and performs species-level comparative analysis, co-occurrence testing, and correlation mapping between defence system presence, resistance gene load, and mobile genetic element distribution.

Key finding: Specific defence systems — particularly Gao_Qat — co-occur with multiple resistance determinants at rates significantly above background, suggesting shared genomic neighbourhoods that may facilitate simultaneous acquisition of defence and resistance. SspBCDE was consistently enriched in A. baumannii clinical isolates, implicating it as a factor in this pathogen's clinical persistence.

Stack: R · DESeq2 · ggplot2 · Statistical correlation and enrichment analysis

Benchmarking differential expression analysis across two computational stacks

Most bioinformatics teams have a preferred language for RNA-seq analysis, but the performance and reproducibility differences between DESeq2 (R) and Python-based implementations are rarely documented systematically. This project runs matched datasets through both stacks and documents where results diverge, where they agree, and what drives the differences — aimed at producing a reproducible reference for teams making implementation decisions.

Stack: R · DESeq2 · Python · edgeR · Bash

Three peer-reviewed papers spanning COVID-19 diagnostics, antimicrobial resistance, and microbiome analysis:

• Takke A, Zarekar M, Muthuraman V, et al. (2022). Comparative study of clinical features and vaccination status in Omicron and non-Omicron infected patients during the 3rd wave in Mumbai. Journal of Family Medicine and Primary Care, 11(10), 6135–6142. DOI

• Daswani P, Muthuraman V, et al. (2020). Effect of Psidium guajava (guava) leaf decoction on antibiotic-resistant clinical diarrhoeagenic isolates of Shigella spp. International Journal of Enteric Pathogens, 8(4), 122–129. DOI

• Jnana A, Muthuraman V, et al. (2020). Microbial community distribution and core microbiome in successive wound grades of individuals with diabetic foot ulcers. Applied and Environmental Microbiology, 86(6), e02608-19. DOI

Before moving into computational work full-time, I spent three years in active research and clinical laboratory environments:

• ICMR – National Institute of Immunohaematology — scaled COVID-19 RT-qPCR testing from 100 to 300+ samples/day through workflow automation; built the QC monitoring infrastructure used across the lab's 24/7 operations
• The Foundation for Medical Research — AMR research on MDR Shigella; designed and validated the 96-well screening assay that underpins the published findings on guava leaf extract
• Manipal School of Life Sciences — characterised wound microbiome dynamics in diabetic foot ulcers using 16S rRNA sequencing and QIIME2; the dataset and pipeline from this work were published in Applied and Environmental Microbiology

This background shapes how I approach computational problems — I know what the data represents before it enters the pipeline, which changes the questions you ask of it.

MSc Bioinformatics — Teesside University (2025) MSc Molecular Biology & Human Genetics — Manipal University (2017)