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Dr. Mohamed El Hadidi is an Assistant Professor of Bioinformatics and Head of the Bioinformatics research group at the center for informatics sciences (CIS), the School of Information Technology, and Computer Science (ITCS) at Nile University since January 2017. El-Hadidi received interdisciplinary, international education and has over six years of experience in biotechnology fields, followed by ten years of experience in computational biology and bioinformatics fields. El-Hadidi received his Ph.D. Degree in Bioinformatics in 2016 from the Department of Computer Science, Faculty of Science, Eberhard Karls Universität Tübingen, Germany. Besides doctoral studies, From 2012-2016, he worked as an assistant lecturer at the same University in Germany.
El Hadidi was awarded an Erasmus Mundus Scholarship to finish his European MSc degree. He had a dual master's degree, First in Biotechnology from the Department of Bioengineering, Instituto Superior Técnico (IST), Technical University of Lisbon, Portugal, and 2nd MSc. in Computational and Systems Biology from the Department of Computer Science, School of Science and Technology, Aalto University, Finland. El-Hadidi has contributed towards the development of academic programs at Nile University, In 2018, he initiated the bioinformatics postgraduate diploma in Bioinformatics, and he is currently the director of the Biomedical Informatics undergraduate program. His research expertise falls in the area of applied bioinformatics, with a focus on Next Generation Sequencing (NGS) data analysis and metagenomics. El Hadidi is an expert in microbiome data analysis for various medical and environmental applications. He has several publications in prestigious international journals and conferences. Besides his academic career, El-Hadidi has gained significant experience in the bioinformatics industry during his role as the head of the Bioinformatics Unit of Colors Medical Laboratories in Egypt.
1) Received DAAD Fellowship for Postdoc in Germany.
2) Awarded Erasmus Mundus Scholarship to finish a dual Master's Degree.
3) Best paper award (2017) in Plos Computational Biology Journal.
Comparative 16S Metabarcoding of Nile Tilapia Gut Microbiota from the Northern Lakes of Egypt
Nile tilapia, Oreochromis niloticus, is the principal fish bred in Egypt. A pilot study was designed to analyze the bacterial composition of the Nile tilapia fish guts from two saltwater lakes in Northern Egypt. Fish samples were obtained from two Delta lakes: Manzala (ML) and Borollus (BL). DNA was extracted, and the bacterial communities in the stomach content were classified (down to the
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
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
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
In-Silico Comparative Analysis of Egyptian SARS CoV-2 with Other Populations: A Phylogeny and Mutation Analysis
In the current SARS-CoV2 pandemic, identification and differentiation between SARS-COV2 strains are vital to attain efficient therapeutic targeting, drug discovery and vaccination. In this study, we investigate how the viral genetic code mutated locally and what variations is the Egyptian population most susceptible to in comparison with different strains isolated from Asia, Europe and other
Insilico Codon Bias Correction for Transgenic Biological Protein Sequences for Vaccine Production
Codon optimization is primarily used in enhancing the levels of protein expression in the host species. Each species has its own codon usage bias, which represents the codons abundance frequency in that species. Using the host usage profile contributes to personalize the synthesis of the DNA vaccines that can achieve highly active vectors the host cells. For optimizing protein expression levels in
Convolutional Neural Network with Attention Modules for Pneumonia Detection
In 2017, pneumonia was the primary diagnosis for 1.3 million visits to the Emergency Department (ED) in the United States. The mortality rate was estimated to be 5%-10% of hospitalized patients, whereas it rises to 30% for severe cases admitted to the Intensive Care Unit (ICU). Among all cases admitted to ED, 30% were misdiagnosed, and they did not suffer from pneumonia, which raises a flag for
Detection of Mammalian Coding Sequences Using a Hybrid Approach of Chaos Game Representation and Machine Learning
Mammalian protein-coding sequence detection provides a wide range of applications in biodiversity research, evolutionary studies, and understanding of genomic features. Representation of genomic sequences in Chaos Game Representation (CGR) helps reveal hidden features in DNA sequences due to its ability to represent sequences in both numerical and graphical levels. Machine learning approaches can
Genotypic characterization of multiple drug resistant Escherichia coli isolates from a pediatric cancer hospital in Egypt
Infection with multiple drug resistant (MDR) Escherichia coli poses a life threat to immunocompromised pediatric cancer patients. Our aim is to genotypically characterize the plasmids harbored in MDR E. coli isolates recovered from bacteremic patients of Children’s Cancer Hospital in Egypt 57357 (CCHE 57357). In this study, 21 carbapenem-resistant E. coli (CRE) isolates were selected that exhibit
- Genomic Data Analytics