Research Group Staff
Bioinformatician
Current
Her name is Mennatolla, but you can call her Menna. Menna was born and raised in the US, came from Oman, with Egyptian background, worked in Singapore and traveled many countries. She sees something truly magical about immersing herself in different cultures, trying new experiences in the beauty of diverse landscapes.
Menna is a bioinformatician driven by the fusion of biology and computational science with a background in computer science and analytics. Throughout her academic journey, she has developed a strong foundation in both fields, allowing to combine her expertise in computational techniques with analytical approaches to tackle complex biological problems. Whether Menna is analyzing data, developing algorithms, or collaborating with interdisciplinary teams, her passion lies in leveraging technology to unlock the mysteries of the natural world.
Beyond academic and professional interests, Menna finds joy and fulfillment in horse riding, outdoor activities like hiking and running, and hitting the gym.
Menna's research interests lie in utilizing computational approaches to investigate the intricacies of biological systems, with a specific focus on understanding the dynamic organization of chromatin and its implications for gene regulation. She is particularly intrigued by the role of chromatin compartments in shaping the three-dimensional structure of the genome and modulating gene expression patterns.
BS in computer science, College of Science, Sultan Qaboos University, Oman
MS in Analytics, College of Engineering, Georgia Institute of Technology, Atlanta, USA
Menna's journey into computational biology began during her bachelor's graduation project, where she explored Protein subcellular and secreted localization prediction using deep learning. It was her graduation project and here started the passion. Moreover, Menna immersed herself in two additional projects that further expanded her expertise. She has worked in two projects in protein contextual representation using masked language modeling in drug target interaction prediction and in Structural embedding of protein in drug target affinity prediction using biformer.
These projects not only provided invaluable hands-on experience but also fueled her enthusiasm for computational biology. They underscored the transformative potential of computational approaches in advancing our understanding of biological systems and driving innovation in drug discovery and development. As she continues to explore this dynamic field, Menna is excited to contribute to further advancements at the intersection of computational techniques and biological research.