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- Presents readers with several types of dynamic representative applications

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- Presents readers with several types of dynamic representative applications

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- Presents readers with several types of dynamic representative applications