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Mathematical Modeling in Bioscience: Theory and Applications provides readers with the tools and techniques needed for mathematical modeling in bioscience through a wide range of novel and intriguing topics. The book concentrates on larger elements of mathematical modeling in bioscience, including topics such as modeling of the Topp-Leone new power generalized Weibull-G distribution family, vector-borne disease modeling, transmission modeling of SARS-COV-2 among other infectious diseases, pattern formulation models, compartmental models for HIV/AIDS transmission, population models, irrigation scheduling models, and predator-prey models. Readers will discover a variety of new methods, approaches, and techniques, as well as a wide range of applications demonstrating key concepts in bioscience modeling. The book provides a leading-edge resource for researchers in a variety of scientific fields who are interested in mathematical modeling, including mathematics, statistics, biology, biomedical engineering, computer science, and applied sciences. Provides key concepts for advanced mathematical methods for modeling in bioscience Includes statistical, delay, random, and stochastic mathematical models Focuses on broader aspects of mathematical models in bioscience Provides readers with several types of dynamic representative applications
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