I am Abdullah Al Marzan, a molecular biologist and bioinformatician focused on bridging bench science with computational precision. My work combines molecular biology, clinical data science, and deep learning to create scalable solutions for diagnostics and translational research.

I completed my BSc and MSc in Molecular Biology at Shahjalal University of Science and Technology (SUST), Bangladesh. My MSc thesis addressed diagnostic methods for Premature Rupture of Membrane (PROM) in low‑resource settings, integrating wet‑lab validation with epidemiological modeling.

Professionally, I have worked as a Clinical Data Manager on a Phase III RCT, where I developed automated monitoring systems, optimized eCRFs, and built real‑time dashboards. As a Medical Research Officer, I contributed to projects on cervical cancer screening, HPV vaccination, PROM biomarkers, and antimicrobial resistance, gaining hands‑on experience with qRT‑PCR, ELISA, and molecular assays.

In parallel, I serve as a Remote Bioinformatician at SUST, focusing on deep learning for miRNA–RNA prediction, molecular dynamics simulations, and computational drug design. I also contributed to Covid‑19 testing and wastewater epidemiology pipelines, as well as cyanobacteria‑based bioremediation projects.

I have co‑authored 12+ peer‑reviewed publications in journals such as Scientific Reports, Frontiers in Pharmacology, and Environmental Pollution, covering viral evolution, miRNA profiling, and epidemic preparedness.

My technical expertise spans Python, R, SQL and SPSS, along with bioinformatics tools such as RNAfold, ViennaRNA, RNAhybrid, IEDB, and GROMACS. I have developed predictive models for RNA–protein interactions, automated clinical trial dashboards, and deep learning pipelines for molecular diagnostics.

I am committed to open science. My deployed miRNA–RNA Interaction Tool is freely accessible, and the source code is available on GitHub .

Looking ahead, my goal is to pursue a PhD in the biological sciences where I can apply my combined expertise in molecular biology, bioinformatics, and data‑driven modeling. I am highly adaptable across both wet‑lab and computational research, and I am eager to contribute to projects that advance innovative, precise, and impactful solutions in life science and health research.