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19972026
most citedApplications of Deep Learning and Reinforcement Learning to Biological Data

876 citations

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11 papers · 1 filter

math.AP2019

Boundary perturbations and steady states of structured populations

Àngel Calsina, József Z. Farkas

In this work we establish conditions which guarantee the existence of (strictly) positive steady states of a nonlinear structured population model. In our framework the steady stat…

math.AP2015★ 1 cited

Mathematical Analysis of a Clonal Evolution Model of Tumour Cell Proliferation

József Z. Farkas, Glenn F. Webb

We investigate a partial differential equation model of a cancer cell population, which is structured with respect to age and telomere length of cells. We assume a continuous telom…

math.AP2015★ 16 cited

Structured populations with distributed recruitment: from PDE to delay formulation

Àngel Calsina, Odo Diekmann, József Z. Farkas

In this work first we consider a physiologically structured population model with a distributed recruitment process. That is, our model allows newly recruited individuals to enter…

math.AP2015★ 7 cited

On a strain-structured epidemic model

Àngel Calsina, József Z. Farkas

We introduce and investigate an SIS-type model for the spread of an infectious disease, where the infected population is structured with respect to the different strain of the viru…

math.AP2011★ 33 cited

Steady states in a structured epidemic model with Wentzell boundary condition

Angel Calsina, Jozsef Z. Farkas

We introduce a nonlinear structured population model with diffusion in the state space. Individuals are structured with respect to a continuous variable which represents a pathogen…

math.AP2010★ 33 cited

Physiologically structured populations with diffusion and dynamic boundary conditions

J. Z. Farkas, P. Hinow

We consider a linear size-structured population model with diffusion in the size-space. Individuals are recruited into the population at arbitrary sizes. The model is equipped with…