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Mariam Oweda Kamel


Faculty Building

Dr. Tarek Khalil Building (UB 1)

Office Number



Mariam Oweda is a bioinformatics researcher at Nile University. She received her B.Sc. degree from Biotechnology college at Misr University for Science & Technology (MUST) followed by two years of experience as a bioinformatics and genomics teaching assistant at Biotechnology college, MUST. Taking the extra mile in the bioinformatics field, she completed her master's degree in the Informatics program at Nile University. Currently, she is working on analyzing OMICS data working with a high-caliber bioinformatics research team at Nile University. Her main interest is understanding Alzheimer's disease using integrative OMICS approaches.

Recent Publications

Positive selection as a key player for SARS-CoV-2 pathogenicity: Insights into ORF1ab, S and E genes

The human β-coronavirus SARS-CoV-2 epidemic started in late December 2019 in Wuhan, China. It causes Covid-19 disease which has become pandemic. Each of the five-known human β-coronaviruses has four major structural proteins (E, M, N and S) and 16 non-structural proteins encoded by ORF1a and ORF1b together (ORF1ab) that are involved in virus pathogenicity and infectivity. Here, we performed

Artificial Intelligence

Benchmarking of Antimicrobial Resistance Gene Detection Tools in Assembled Bacterial Whole Genomes

Antimicrobial resistance (AMR) is one of the ten dangers threatening our world, according to the world health organization (WHO). Nowadays, there are plenty of electronic microbial genomics and metagenomics data records that represent host-associated microbiomes. These data introduce new insights and a comprehensive understanding of the current antibiotic resistance threats and the upcoming

Artificial Intelligence

Potential probiotics for viral triggered type 2 diabetes

The scientific literature is full of studies that provide evidence highlighting the role of microbiome in type 2 diabetes (T2D) development and progression, still, discrepancies are evident when studying the link between certain taxonomic groupings and T2D, thus, eliminating the discrepancy between such studies is crucial to build on a robust systematic approach to identify the possible linkage

Artificial Intelligence
Research Tracks
  • Bioinformatics
  • Systems Biology
  • Neuroscience
  • Multi-omics Data Integration