Biology undergraduate at METU with a strong interest in bioinformatics and biotechnology, where I merge laboratory knowledge with computational problem-solving. Passionate about extracting insights from protein and DNA sequences NGS data, and biological datasets.
Skilled in Python, R, and Java, with experience building backend systems, APIs, and cloud-based pipelines using Docker, AWS, and GCP. I aim to bridge biology and technology by applying computational tools to real-world challenges in biotech and biomedical research.
A strong foundation in Python, R, and Java supports my work in algorithms, statistics, and machine learning, with applications in bioinformatics, genomics, and computational biology.
Skilled in NGS pipelines, covering QC, trimming, alignment, SAM/BAM/BED handling, peak calling (ChIP-seq), DEG and enrichment analysis (RNA-seq), functional insights through GO/KEGG, correlation studies, and visualization with IGV, with hands-on experience in both Linux and Galaxy environments.
Experienced in deploying applications with Docker and managing scalable workflows on AWS and GCP. Skilled in CI/CD practices and cloud integration to support bioinformatics and backend systems.
Experienced in sequence analysis using BLAST, BLAT, CLUSTAL O, pairwise/ multiple alignments, motif discovery (MEME Suite), and EMBOSS tools. Skilled in leveraging UCSC Genome Browser, Ensembl, PDB, AlphaFold, and Chimera for structural and functional insights.
Skilled in building robust backend systems using Django, Flask, and FastAPI. Experienced in designing and integrating REST APIs for scalable applications and data-driven workflows.
Proficient in designing and managing databases using MongoDB, PostgreSQL, and SQLite. Experienced in querying, structuring, and optimizing data for backend applications.