Bioinformatics and Computational Biology Unit-Zewail City

Check our recent publication in npj Systems Biology and Applications. Our paper entitled "A multi-omics approach for biomarker discovery in neuroblastoma: a network-based framework" proposes an integrated computational framework with three levels of high-throughput Neuroblastoma data to identify candidate biomarkers. We show that analyzing cellular interactome to identify potential biomarkers is a promising approach that can contribute to optimizing efficient therapeutic regimens to target NB vulnerabilities.

A multi-omics approach for biomarker discovery in neuroblastoma: a network-based framework - npj Systems Biology and Applications Neuroblastoma (NB) is one of the leading causes of cancer-associated death in children. MYCN amplification is a prominent genetic marker for NB, and its targeting to halt NB progression is difficult to achieve. Therefore, an in-depth understanding of the molecular interactome of NB is needed to impr...

Check out our latest publication “AI In Healthcare: Using Bayesian Networks To Predict Response To Immune Checkpoint Blockades”

Cancer remains a leading cause of death worldwide, with its heterogeneous and patient-specific nature complicating treatment. Immunotherapy, especially immune checkpoint blockades (ICB), shows promising potential by reactivating the immune system to detect and destroy cancer cells. However, their effectiveness largely depends on the patient’s clinical and molecular characteristics, making them unsuitable for everyone. This highlights the importance of developing predictive and interpretable models that could distinguish potential responders from non-responders. This study aims to utilize gene expression data to predict patients’ responses to ICB and identify key genes whose expression is associated with treatment outcome using probabilistic Bayesian networks (BNs). To address the high-dimensional nature of gene expression data, we propose and compare the use of machine learning-based feature selection (FS) and clustering by weighted gene co-expression network analysis (WGCNA). To our knowledge, this is the first study to apply BNs along with FS and WGCNA dimensionality reduction techniques to tackle ICB response using transcriptomic data. We achieved a maximal classification accuracy of 75% and identified eight genes and two gene clusters directly influencing ICB response. These results may offer more biological insights and mechanisms underlying ICB response. The proposed pipeline will contribute to guiding treatment decisions, minimizing harmful side effects, and reducing the financial costs associated with ineffective treatments.

AI In Healthcare: Using Bayesian Networks To Predict Response To Immune Checkpoint Blockades | IEEE Conference Publication | IEEE Xplore Cancer remains a leading cause of death worldwide, with its heterogeneous and patient-specific nature complicating treatment. Immunotherapy, especially immune c

Check out our latest publication in collaboration with Center for Genomics at Zewail City.

Recombination-mediated dissemination of Methicillin-resistant S. aureus clonal complex 1 in the Egyptian health care settings - Annals of Clinical Microbiology and Antimicrobials Background Methicillin-resistant Staphylococcus aureus (MRSA) is a rapidly evolving pathogen that is frequently associated with outbreaks and sustained epidemics. This study investigated the population structure, resistome, virulome, and the correlation between antimicrobial resistance determinants....

We have some exciting news! On September 25th, Radwan Derbala, a master’s student and a research assistant in the Bioinformatics and Computational Biology (BCB) Unit, and Ahmed Saadawy, a senior undergraduate student of Computational Biology and Genomics and a junior research assistant in the BCB were honored with one of the best poster awards at the first German-Arab Symposium on Bioinformatics, organized by the German-Arab Research Network for Computational Life Science GARN CLS, for their work on "Prognostic Significance of M1 Macrophages in Triple-negative Breast Cancer". The aim of the project is to investigate the tumour immune microenvironment of triple-negative breast cancer, aiming to identify immune cell-related prognostic biomarkers. The GARN-CLS is an initiative funded by the DAAD and the federal foreign office of Germany to foster global collaboration and interdisciplinary research among German and Arab institutions.

Check out our paper about deep learning with a focus on medical imaging segmentation.

Deep Learning for Image Segmentation: A Focus on Medical Imaging Image segmentation is crucial for various research areas. Many computer vision applications depend on segmenting images to understand the scene, such as autonomous driving, surveillance systems, robotics, and medical imaging.... | Find, read and cite all the research you need on Tech Science Press

Our recent article published in Scientific Reports - Nature entitled, "SARS-CoV-2 potential drugs, drug targets, and biomarkers: a viral-host interaction network-based analysis". We sought potential biomarkers, drug targets, and repurposed drugs through human mRNA-miRNA and human-virus interaction networks.

SARS-CoV-2 potential drugs, drug targets, and biomarkers: a viral-host interaction network-based analysis - Scientific Reports COVID-19 is a global pandemic impacting the daily living of millions. As variants of the virus evolve, a complete comprehension of the disease and drug targets becomes a decisive duty. The Omicron variant, for example, has a notably high transmission rate verified in 155 countries. We performed inte...

30 minutes are left for meeting Computational Biologist in industry.
https://forms.gle/afm34n6PKchCPojQ7

Working as a bioinformatics Consultant at QuantBio, LLC ,North Carolina or bioinformatics software engineer at SelfDecode, US, or start your own business in Egypt in your early twenties is not a dream. There is a whole different world with many industrial careers ahead of you as a computational biologist. It is not just academia!
Join us next Saturday at 7 pm and meet computational biologists in industry.
Omar Abdelwahab: Bioinformatics Consultant at QuantBio, LLC, USA
Abdullah Amr: Bioinformatics software engineer at SelfDecode, USA
Sara Badawy: Structural Bioinformatician at Proteinea, Egypt
For meeting link, please register by filling in this form
https://forms.gle/afm34n6PKchCPojQ7

We are sorry to inform you that we will do postpone our next talk titled" The future prospects of a computational biologists in Industry" in order to mourn the loss of our beloved Sara Akram. We appreciate your thoughts and prayers. Thank you

Computational Biology Alumni Mini-Talks Series: The future prospects of a computational biologists in Industry
Dearest Zewailans and Future Scientists,
Computational Biology Alumni Mini-Talks Series: The future prospects of computational biologists in Industry talk of Computational Biology Alumni Mini-Talks Series to know more about how computational biologists excel in the industry. You will meet ZC alumni talking about their work in the industry. You will have the chance to ask them questions you have in mind. If you are interested, please register for the next talk by filling out this form (https://forms.gle/afm34n6PKchCPojQ7).
Timing: March, 15th, 2022 at 12:30 pm
Venue: at ZC (room will be announced soon)
Guests:
Mohamed Elkerdawy (Computational Lead, Proteinea, Egypt)
Omar Abdelwahab (Bioinformatics Consultant, QuantBio,LLC, USA)
Registration to the talk: https://forms.gle/afm34n6PKchCPojQ7
This is an internal event for Zewail students