BIO-MATHEMATICAL MODELING UNDER UNCERTAIN ENVIRONMENT provides an interdisciplinary framework for studying design and analysis of mathematical and biological modeling in uncertain environment. This edited volume has thirteen illustrated bio-mathematical models covering the area of stability of ecosystem, eco-epidemiological model, SIS model, SIR model, etc. The bifurcation theory for dynamical system including basic reproduction number and phase diagram is also developed in a progressive manner. Specially, the diverse cancer types (like breast cancer, lung cancer, prostate cancer, colon cancer, etc.) model, tuberculosis model with exogenous re-infection, Cholera Epidemic model, pre-predator model, harvesting model (for fish, broiler and duck) and bio-economical model are developed in a progressive manner with the aim of developing a deeper understanding of the stability analysis and their control. This book can be used by under graduate and post graduate students, researchers of different fields, professional scientists and engineers to enrich their knowledge about stability theory, bio-mathematical modeling and uncertain theory.

Mathematical Modelling and Ecology / Stability Analysis of a Dynamical System / An Overview on Stability Analysis of a Nonlinear System and its Application in Prey-Predator Model / Mathematical Analysis of an SIR Epidemic Model with Saturated Treatment Function / Study of a Reaction-Diffusion Eco-Epidemiological Model Under the Influence of Non-Local Delay / A Combined Project of Fish, Broiler and Ducks: Dynamical System with Interval Biological Parameters / Dynamical Behavior of a Tuberculosis Epidemic Model and the Influence of Backward Bifurcation / The Dynamics of a Cholera Epidemic Model with Some Control Parameters / Bio-Economic Prey-Predator Model with Reserve in Prey / Behavior of Distributed Delay in an SIR Model Where Medical Resource Supplied / Comparative Analysis of Popular Tools Used for miRNA Target Prediction / Modelling of Ecosystem Using Graph Theory / Review on Optimal Control Problems for Bio-Mathematics in Uncertain Environments.

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