Mathematical Modeling in Bioscience: Theory and Applications provides readers with tools and techniques 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. The 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. This 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.
Table of Contents
1. Analysis of the Impact of Time Delay Incorporation in Mathematical Models of Cellular Population Dynamic2. Alternatives food for predators: Elucidating their impact on a predation model with Allee effect on prey
3. Modeling and analysis of an eco-epidemiological model with Caputo-Fabrizio derivative
4. The Topp-Leone-Exponentiated Half Logistic-Generalized-G Family of Distributions with Applications
5. A mathematical model for the dynamics of Visceral Leishmaniasis disease with time delay
6. Fractalization through stochasticization processes in epileptic dynamics
7. Mathematical Model of Alzheimer Disease with Nonlocal and Nonsingular derivative
8. From Bubble Nucleation to Oscillatory Denaturation: Understanding Complex DNA Dynamics through Nonlinear Modeling
9. An inertial projective Mann algorithm for solving split equilibrium problems with application to Parkinson’s disease screening
