Yasser El-Manzalawy, PhD
Dr. El-Manzalawy is a faculty member in the departments of Imaging Science & Innovation and Biomedical & Translational Informatics. His research focuses on developing and disseminating innovative methods, frameworks and resources for supporting integrative and predictive analyses of biomedical data including genomics, omics, microbiome, imaging, environmental and wearables to better understand the biology and underlying mechanisms of complex diseases and treatments.
His long-term research goal is to advance our understanding and make sense of big data in life and health sciences through developing and applying integrative informatics tools and methodologies to enable and accelerate translational science.
To date, he has developed several novel algorithmic solutions and machine learning based tools for vaccine informatics, structural bioinformatics, genomics, metagenomics, multi-omics data integration and mHealth.
- Jung, Y., El-Manzalawy, Y., Dobbs, D., & Honavar, V. (2019). Partner-specific prediction of RNA-binding residues in proteins: A critical assessment. Proteins: Structure, Function and Bioinformatics, 87(3), 198-211.
- Abbas, M., Le, T., Bensmail, H., Honavar, V., & El-Manzalawy, Y., (2018). Microbiomarkers discovery in inflammatory bowel diseases using network-based feature selection. In Proceedings of the 2108 ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (pp. 172-177).
- El-Manzalawy, Y., Hsieh, T.Y., Shivakumar, M., Kim, D., & Honavar, V. (2018). Min-redundancy and max-relevance multi-view feature selection for predicting ovarian cancer survival using multi-omics data. BMC medical genomics, 11(3), 71.
To learn more about his work, visit:
PhD, Computer Science from Iowa State University.