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General Information

Full Name Sarath Kumar Murugan
Location Huddinge, Sweden
Phone (+46) 764307294
Date of Birth 07/05/1996
Languages English, Tamil

Experience

  • Jan 2023 - Present
    Bioinformatician (Full Time)
    Prostate Cancer Research Group, Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet, Stockholm, Sweden
    • Designed and maintained scalable pipelines (Nextflow, Snakemake) for genomic and transcriptomic profiling of cancer patients.
    • Optimized structural variant workflows for liquid biopsy data, improving accuracy and reproducibility.
    • Built a web application for clinical variant curation to streamline precision oncology workflows.
    • Administered and optimized HPC clusters and containerized workflows for large-scale analyses.
    • Deployed a digital slide archive for reviewing whole-slide images (WSI) for pathologists.
    • Supported clinical trials including ProBio, iPCM, and PSFF.
  • Nov 2020 - Dec 2022
    Bioinformatician (Part Time)
    Prostate Cancer Research Group, Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet, Stockholm, Sweden
    • Developed pipelines for targeted re-sequencing and whole-genome sequencing using Snakemake.
    • Analyzed single-cell RNA-seq and spatial transcriptomics (Seurat, Scanpy, Squidpy).
    • Set up cloud-based bioinformatics infrastructure for routine analysis.
  • Jan 2020 - Oct 2020
    Research Assistant
    Biostatistics Research Group, Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet, Stockholm, Sweden
    • Developed FuSeq_WES, a statistical method for detecting gene fusions in WES and targeted data.
    • Validated and optimized the method on patient datasets and released it on GitHub.
  • May 2019 - Dec 2019
    Bioinformatician
    Clinical Genomics Facility, Science for Life Laboratory, Stockholm, Sweden
    • Upgraded BALSAMIC, a Snakemake-based cancer pipeline for targeted resequencing.
    • Implemented automated testing (pytest) and benchmarking (Illumina hap.py); built validation workflow (BALSAMIC Validate).
    • Developed an interactive CNV visualization tool (CNVPlots) and deployed on Heroku.
  • Nov 2018 - May 2019
    Bioinformatician
    Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet, Stockholm, Sweden
    • Enhanced an in-house Python framework for targeted cancer panel sequencing.
    • Automated liquid biopsy analysis steps; built interactive result visualization (Flask, JavaScript).
    • Led software testing and documentation for pipelines.
  • Jun 2017 - Oct 2018
    Junior Bioinformatics Programmer
    Genome Life Sciences Pvt. Ltd., Chennai, India
    • Developed pipelines for WGS, WES, and mRNA-seq within a cloud-based NGS analysis and clinical reporting platform (Genome Explorer).
    • Identified SNPs, indels, SVs, and DEGs using shell scripting; performed DGE and Trio analyses.
    • Integrated Clinical Variant Classification (CVC) for pathogenicity prediction.

Education

  • 2020 - 2022
    M.Sc (Bioinformatics) - Grade 1.5 (Excellent)
    Saarland University, Saarbrücken, Germany
    • Advanced coursework in AI, Machine Learning, Software Engineering, and Single-Cell Bioinformatics.
    • Master's Thesis - "MethylTFR — A computational method to identify DNA methylation signatures in transcription factor binding sites."
  • 2013 - 2017
    B.Tech (Bioinformatics) - CGPA 8.07/10
    Tamil Nadu Agricultural University, Coimbatore, India
    • Built a database for bacterial and fungal stress-responsive genes in rice to support gene-phenotype association.
    • Developed a real-time web application for post-counselling undergraduate admissions (PHP, MySQL), adopted for TNAU's 2016 intake.

Academic Interests

  • Cancer Genomics & Precision Oncology
    • Variant discovery, structural variants, clinical interpretation
  • Transcriptomics & Spatial Omics
    • Bulk RNA-seq, scRNA-seq, spatial transcriptomics
  • Epigenomics & Multi-Omics
    • Integration of methylation and expression for biomarker discovery
  • ML/AI for Omics
    • Predictive modeling and workflow integration for translational research
  • Workflow Engineering & Reproducibility
    • Scalable pipelines, containers, testing, CI/CD, HPC/Cloud