🧬 Graduate Student in Biotechnology | Passionate about computational biology and bioinformatics

I'm a graduate student combining wet-lab biology with computational approaches to tackle real-world health challenges. My work focuses on using data science and bioinformatics to understand infectious diseases and genomic patterns.

• 🦠 Currently working on dengue virus genomic surveillance and variant tracking
• 💻 Building interactive dashboards and tools for biological data analysis
• 📊 Applying statistical methods and data visualization to genomic datasets
• 🌍 Contributing to public health research through open-source bioinformatics

Programming & Analysis:

• R (Shiny, Bioconductor, tidyverse, data visualization)
• Git/GitHub version control
• Bash scripting
• Data cleaning and statistical testing

Bioinformatics:

• Genomic sequence analysis
• Variant detection and tracking
• Phylogenetic analysis
• Quality control and motif detection
• Comparative genomics

Tools & Platforms:

• R Shiny dashboards
• Bioconductor ecosystem
• Reference genome alignment
• Data visualization (ggplot2, plotly)

Interactive R Shiny dashboard analyzing 13 real DENV-2 sequences from the 2023 Bangladesh dengue outbreak (Dhaka & Chattogram isolates). Features QC filtering, motif detection, and modern visualization for genomic surveillance.

Prototype version for general dengue motif and variant tracking using reference strains (NC_001477.1 Dengue Virus 1, NC_001474.2 Dengue Virus 2). Foundation for genomic epidemiology tools.

Morphometric analysis demonstrating data cleaning, statistical testing, and visualization in R - showcasing reproducible research practices in biological datasets.

Bridging code and biology through R - exploring Bioconductor for genomic data analysis.

Comparative analysis of coding vs non-coding regions and GC content in the Saccharomyces cerevisiae genome using R.

• Bioinformatics & Computational Biology: Developing tools for genomic data analysis
• Structural Genomics: Understanding genome organization and evolution
• Infectious Disease Genomics: Tracking pathogen variants and evolution
• Computational Drug Design: In silico approaches to drug discovery
• Data Science for Life Sciences: Applying statistical methods to biological questions

• 📧 Email: faiyaj.mdabrar@gmail.com
• 🔗 ORCID: 0009-0005-9646-4508
• 💼 Open to collaborations in bioinformatics, genomics, and computational biology!

⭐️ Feel free to explore my repositories and reach out if you'd like to collaborate on bioinformatics projects!