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Home / Journals / Advances in Bioscience and Bioengineering / Mathematical and Statistical Modeling of Biological Systems
Mathematical and Statistical Modeling of Biological Systems

Special Issue Flyer (PDF)

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Lead Guest Editor:
Mostafa Abo Elsoud
Microbial biotechnology, Giza, Al Jizah, Egypt
Guest Editors
Enas Mostafa
Biotechnology and Genetic Engineering Pilot Plant Unit, National Research Centre
Giza, Egypt
Mohammed Ibrahim
Biotechnology and Genetic Engineering Pilot Plant Unit, National Research Centre
Giza, Egypt
Ahmed Gabr
Plant Biotechnology Department, National Research Centre
Giza, Egypt
Abdullah Adel
Pharmaceutical industry research division, National Research Centre
Giza, Egypt
Snehasis Jana
Trivedi Science Research Laboratory Pvt. Ltd
Bhopal, Madhya Pradesh, India
Ijege Odigiri
Department of Applied Sciences, Kaduna Polytechnic
Kaduna, Nigeria
Introduction
In most industrial biotechnology, the optimization of any process conditions is generally done by varying one factor at a time approach. This approach is simple, easy and understandable by general practitioners. However, this strategy is laborious and time consuming, especially for a large number of variables and often do not consider interactions among variables. Individual and interactive effects enable each reaction parameter to be optimized in coherence with others. Alternatively, mathematical modeling can be used. Mathematical models are tools that we can use to describe the past performance and predict the future performance of biotechnological processes. They can be applied to processes operating at many different levels, from shake flask to the commercial/industrial scale. Mathematical models can be powerful tools in both fundamental research and applied research and development. Mathematical modeling has become an important tool to understand and unravel biological complexity. Mathematical and statistical modeling became an important tool for conducting researches concerning hazard and toxic materials and costly researches. Through this special issue, we aim to illustrate the processes of mathematical and statistical modeling in biotechnological systems using real experiments and results. Also, we aim to discuss the processes in the light of the obtained results from the mathematical and statistical models.

Aims and Scope:

  1. Make Mathematical modeling more familiar
  2. New trends in Biotechnology
  3. Methods of Bioprocess improvement
  4. Role of engineering in biological science
  5. Opening the road for the emerging biotechnologies
  6. Conclusions based on Mathematical models
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