Rahnuma Tabassum is an undergraduate student of Biochemistry and Molecular Biology at Jagannath University, Bangladesh, with strong training in both experimental and computational biomedical research.She worked as an internee in the GSA Bioinformatics Internship 2025, organized by GNOBB, SPSB, and ASI School of Life in collaboration with Chiral Bangladesh and DeepBio Limited, demonstrating outstanding dedication and excellence.
Rahnuma showcased her expertise in computational biology through her research titled “Integrated Transcriptomic Meta-Analysis Identifies Pathway Crosstalk and Therapeutic Targets in Liver Hepatocellular Carcinoma.” Her work reflects a strong commitment to advancing data-driven cancer research and inspiring the next generation of bioinformaticians.
In her departmental research, she explores bioactive compounds from Bangladeshi medicinal plants as environmentally friendly larvicidal agents, offering alternatives to conventional insecticides. This research is aligned with the One Health and microbiome framework and supports the development of safer, sustainable public health solutions, including mosquito repellents and nanoparticle-based applications.
In addition to her research activities, she has served in leadership roles, including President of ISCB RSG Bangladesh, and actively engages in academic outreach, mentoring, and educational initiatives.
She is committed to integrating computational and experimental strategies in drug discovery and molecular biology, with the goal of building a career that bridges biological sciences and computational approaches to advance translational biomedical research.
Key Contributions:
- Supports computational biology research projects.
- Creates tutorials and pipelines for protein modeling.
- Assists in training other students and researchers.
- Maintains reproducible code and workflow documentation
Key Takeaways:
- AlphaFold predicts protein structures with high accuracy.
- Useful for research in drug discovery, molecular biology, and bioinformatics.
- Free tools (AlphaFold DB and ColabFold) allow hands-on exploration.
- Understanding AlphaFold helps participants see the future of computational biology.