I work with microbial ecology, multi-omics data analysis, and reproducible workflows in R and Python.
My experience includes 16S metagenomics, functional prediction, targeted transcriptomics, and LC–MS/MS-based lipid data processing.

• Microbiome analysis (skin, scalp, and environmental samples)
• Multi-omics integration (taxonomic, functional, transcript, lipid data)
• Reproducible pipelines (R, Python, Snakemake, Bash)
• Data visualization and statistical analysis

Tools: DADA2, QIIME2, phyloseq, DESeq2, MZmine, Snakemake, FastQC, GROMACS
Databases: SILVA, Greengenes, RefSeq
Methods: Diversity analysis, differential abundance, QC workflows, functional prediction
Languages: R, Python, Bash

• Assembly and long-read analysis: Pipeline for long-read assembly and functional profiling using public datasets.

• Bioinformatics Study Notebooks: Exploratory analyses and templates for microbial and multi-omics workflows.

Some industry projects are not public due to IP restrictions.
Public repositories reflect study materials, workflow templates, and reproducible examples.