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imsarath/README.md

👋 Hi there, welcome to my GitHub!

I’m Sarath Murugan, a bioinformatics programmer passionate about leveraging software engineering, data science, and cloud technologies to solve complex biological and biomedical challenges. My work focuses on building scalable, efficient, and reproducible pipelines for analyzing large-scale genomic and multi-omics datasets. Here, you’ll find:

  • Open-source projects related to bioinformatics, data analysis, and workflow automation.
  • Contributions to collaborative repositories aimed at advancing computational biology.
  • Tools and scripts designed to make biological data processing faster and more accessible.

🔍 What drives me

I believe in the power of computational solutions to accelerate discoveries in life sciences. From genomic data processing to cloud-based pipeline deployment, I enjoy tackling problems that sit at the intersection of biology, programming, and high-performance computing.

🤝 Let’s Collaborate!

I’m always open to collaboration, knowledge sharing, and feedback. If you’re working on something exciting in bioinformatics or cloud-based data analysis, feel free to reach out!

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  1. Clinical-Genomics/BALSAMIC Clinical-Genomics/BALSAMIC Public

    Bioinformatic Analysis pipeLine for SomAtic Mutations In Cancer

    Python 58 15

  2. Deep-Learning-Specialization Deep-Learning-Specialization Public

    This repository contains my completed assignments and solutions for the Deep Learning Specialization offered by Coursera and taught by Andrew Ng.

    Jupyter Notebook

  3. genomic-medicine-sweden/nf-autoseq genomic-medicine-sweden/nf-autoseq Public

    a nextflow pipeline designed for clinical targeted-panel sequencing samples.

    Nextflow 1

  4. nf-capbench nf-capbench Public

    An automated nextflow pipeline for capture kit benchmarking

    Nextflow

  5. pcr_calculator pcr_calculator Public

    R script to calculate Prostate Cancer Risk Score for multiple samples

    R

  6. cnvplots cnvplots Public

    Python web application to create interactive copy number variation plots

    Python 1