DECODING GENOME
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MSc Bioinformatics Candidate | Genomics, RNA-Seq & Computational Biology
A researcher translating raw sequencing data into biological insight — from wet-lab genomics to reproducible computational pipelines.
I'm an MSc Bioinformatics candidate focused on genomics, RNA-Seq and computational biology. My work spans the full arc of modern genomics — from molecular wet-lab techniques to building reproducible analysis pipelines that turn sequencing reads into clinical and biological meaning.
I'm driven by precision medicine and the potential of multi-omics and AI to reshape how we understand disease.
Medical Genomic Research Center — wet-lab genomics & molecular biology.
Statistical modelling, genomics, NGS and applied analysis intensives.
MSc Bioinformatics Candidate, computational & translational genomics.
Hover any node to reveal proficiency. Filter by category to explore clusters of connected expertise.
A genome-browser-inspired view of the analyses I work with — every chart animates as it enters the viewport.
Genes × samples · z-scored
Differential expression
Sample clustering · PC1 / PC2
Normalized counts (TPM)
Gene–gene co-expression graph
Tehran Medical Sciences, Islamic Azad University
Hands-on molecular biology and genomics — from sample preparation and nucleic-acid extraction to amplification, quantification and research support across active projects.
Scroll to illuminate the path — formal study and intensive bioinformatics training.
University of Birmingham
Computational genomics, machine learning for biology, and translational research.
Bioinformatics Training
Regression, inference and experimental design for omics data.
Bioinformatics Training
Foundations of sequencing technologies and genomic data.
Bioinformatics Training
Hands-on alignment, variant calling and expression workflows.
Research directions I'm actively pursuing at the intersection of genomics, medicine and artificial intelligence.
Decoding tumor heterogeneity and driver mutations from sequencing data.
Integrating genomic, transcriptomic and microbiome layers into unified models.
Translating molecular profiles into individualized therapeutic insight.
Deep learning for sequence, structure and expression prediction.
Surfacing robust, reproducible signatures of disease and response.
Manuscripts in preparation. Forthcoming work will explore transcriptomic biomarkers and multi-omics integration.
Coming soonOpen to research collaborations, PhD opportunities and roles in genomics & computational biology.