Introduction to Mathematical Oncology presents biologically well-motivated and
mathematically tractable models that facilitate both a deep understanding of cancer biology …

Tumor cells develop different strategies to cope with changing microenvironmental
conditions. A prominent example is the adaptive phenotypic switching between cell …

Glioblastoma multiforme is an aggressive brain cancer that is extremely fatal. It is
characterized by both proliferation and large amounts of migration, which contributes to the …

We have derived reaction–dispersal–aggregation equations from Markovian reaction-
random walks with density-dependent jump rate or density-dependent dispersal kernels …

We study positive solutions y (u) for the first order differential equation y= q (cy 1 p− f (u))
where c> 0 is a parameter, p> 1 and q> 1 are conjugate numbers and f is a continuous …

We introduce two models of biological aggregation, based on randomly moving particles
with individual stochasticity depending on the perceived average population density in their …

Reaction-nonlinear diffusion partial differential equations (RND PDEs) have recently been
developed as a powerful and flexible modeling tool in order to investigate the emergence of …

Reaction-nonlinear diffusion (RND) partial differential equations are a fruitful playground to
model the formation of sharp travelling fronts, a fundamental pattern in nature. In this work …

This work is concerned with the properties of the traveling wave of the backward and forward
parabolic equation u< sub> t=[D (u) u< sub> x]< sub> x+ g (u); t≥ 0; x∈ ℝ; where D (u) …

This paper deals with the spatio-temporal dynamics of a pollinator–plant–herbivore
mathematical model. The full model consists of three nonlinear reaction–diffusion–advection …