89 research outputs found
Mathematical modeling of heterogeneous stem cell regeneration: from cell division to Waddington's epigenetic landscape
Stem cell regeneration is a crucial biological process for most self-renewing
tissues during the development and maintenance of tissue homeostasis. In
developing the mathematical models of stem cell regeneration and tissue
development, cell division is the core process connecting different scale
biological processes and leading to changes in both cell population number and
the epigenetic state of cells. This review focuses on the primary strategies
for modeling cell division in biological systems. The Lagrange coordinate
modeling approach considers gene network dynamics within each individual cell
and random changes in cell states and model parameters during cell division. In
contrast, the Euler coordinate modeling approach formulates the evolution of
cell population numbers with the same epigenetic state via a
differential-integral equation. These strategies focus on different scale
dynamics, respectively, and result in two methods of modeling Waddington's
epigenetic landscape: the Fokker-Planck equation and the differential-integral
equation approaches. The differential-integral equation approach formulates the
evolution of cell population density based on simple assumptions in cell
proliferation, apoptosis, differentiation, and epigenetic state transitions
during cell division. Moreover, machine learning methods can establish
low-dimensional macroscopic measurements of a cell based on single-cell RNA
sequencing data. The low dimensional measurements can quantify the epigenetic
state of cells and become connections between static single-cell RNA sequencing
data with dynamic equations for tissue development processes. The
differential-integral equation approach presented in this review provides a
reasonable understanding of the complex biological processes of tissue
development and tumor progression.Comment: 26pages, 1 figure
Moment Boundedness of Linear Stochastic Delay Differential Equation with Distributed Delay
This paper studies the moment boundedness of solutions of linear stochastic
delay differential equations with distributed delay. For a linear stochastic
delay differential equation, the first moment stability is known to be
identical to that of the corresponding deterministic delay differential
equation. However, boundedness of the second moment is complicated and depends
on the stochastic terms. In this paper, the characteristic function of the
equation is obtained through techniques of Laplace transform. From the
characteristic equation, sufficient conditions for the second moment to be
bounded or unbounded are proposed.Comment: 38 pages, 2 figure
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