Theoretical Part Immunity: Organs, Cells, Molecules –Innate Immunity vs Adaptive Immunity –Vaccine Technology –Immunology of Neonates –Synthetic Immunology –immunodiagnostic methods including immunoblotting techniques, viral replication -disease initiation -viruses, molecular mechanisms, and viral genetics. Practical partPractical experience of the production of monoclonal antibodies, production

This course covers the basic concepts required for students to retrieve, manipulate, and analyze biological data available on public online repositories. It provides a useful introductory guide required for furthers high throughput NGS biological data analysis.

Genes Expression Profiling -Model Organisms -Animal and Plant Genome: Evolution, Sequencing, analysis, Assembly -Modelling of Gene Structure –Gene Interactions, Gene Function –Diagnostic Tools of Genomics, Disease Genomics.

This course covers basic Linux OS introduction starting from installation and command line interface to the knowledge required for dealing with the Next Generation Sequencing (NGS) data and numerous analysis software. This course also will introduce different sequencing technologies, various software for data analysis, and online repositories for next generation sequencing (NGS) data.

Introduction –Protein Arrays, Chips, Interaction Mapping, Structure, Function –Disease Proteomics –Lipid Profiling, Types –Glycans, Glycoproteins, Glycobioinformatics' Tools.

Theoretical PartIntroduction, Mechanistic and Modular Approaches, Mathematical Modeling, Graph Classifying Techniques –Properties of Biological Networks –Computational Tools –Metabolic Flux, Networks –Systems Biology for Infectious Disease, Brain Functions and Cancer. Practical PartThe course covers different methodologies for understanding and analyzing biological systems, linking the gap between

This course covers different recent techniques and methods used in computer-aided drug design. The course describes pipelines for drug development and its associated computational chemistry. Additionally, informatics approaches for the prediction of chemical properties, description of lead candidates and datasets are explained. Different software for protein-ligand docking, de-novo design, and

The main goal of this course is to teach students how to take data -that at first glance -has little meaning, process and manipulate it into a form of useful knowledge. Various techniques have been developed for presenting data visually. However, in this course, we will be using several data visualization libraries in Python, namely Matplotlib and Seaborn.

This course explains in depth different concepts of object-oriented programming (OOP) using Python. In addition, other important programming aspects including data structures and algorithms will be covered. The main goal of this course is to prepare students to reach an advanced level in programming. The course explains some of the key algorithms used in the analysis of biological data. The course

This course provides students in the bioinformatics track with an accelerated introduction to the basics of high-performance computing of big data, focusing on biological data as an emerging example of big data. The course covers different trends in big data computing, handling, and processing of big data, solutions for big data computing and recent applications of big data in bioinformatics.

This course covers the basic concepts of machine learning and data mining providing fundamental knowledge about different algorithms used in machine learning and statistical data analysis, key data mining techniques, data mining algorithms over tabular data and application of algorithms over textual data.

This course will introduce at first the colours of biotechnology, then explain every branch of biotechnology in more detail, then new tools helping the evolution of biotechnology, such as databases and automation, will be considered, and finally the mutual impact of the biotechnology on the society and vice versa will be studied, starting from ethics, products, media coverage and reaching the

Cell Cycle and Molecular Regulation -Prokaryotes and Eukaryotes Cell Cycles –Cell Growth –Development of a Tissue –Plasma Membrane and Cell Adhesion, Transport -Cell Communication and Signaling Pathways –Cell Aging, Death and Culture.

Introduce the concepts of cell and tissue culture. Teach the basic knowledge and skills essential to the successful cultivation of plant cells and tissues, and micropropagation of plants Expose the student, using primary cell lines, to sterile technique, media preparation and sterilization. Familiarize the students with cryopreservation. Explore development phenomena in tissue culture cells

Embryology: Animal, Human, Stem Cells –Nuclear and Somatic Cell Genetic Reprogramming –Stem Cells Epigenetics, Therapeutics, Bone Tissue Regeneration, Tissue Scaffolds, Growth Regulation –Mechano-transduction in Stem Cells. Organ transportation in animals –stem cells and artificial organs-animal cloning.

Enable to gain an understanding of the major decisions faced by managers in their efforts to balance the organization’s objective against the needs and opportunities in the global marketplace. Relate theory to practice using an individual or group project throughout the course where students perform a market analysis of a particular Biotechnology product and promotion. Give an understanding of the