Mathematics of neural stem cells: Linking data and processes

IF 3.9 4区 生物学 Q4 Biochemistry, Genetics and Molecular Biology Cells and Development Pub Date : 2023-06-01 DOI:10.1016/j.cdev.2023.203849
Diana-Patricia Danciu , Jooa Hooli , Ana Martin-Villalba , Anna Marciniak-Czochra
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引用次数: 2

Abstract

Adult stem cells are described as a discrete population of cells that stand at the top of a hierarchy of progressively differentiating cells. Through their unique ability to self-renew and differentiate, they regulate the number of end-differentiated cells that contribute to tissue physiology. The question of how discrete, continuous, or reversible the transitions through these hierarchies are and the precise parameters that determine the ultimate performance of stem cells in adulthood are the subject of intense research. In this review, we explain how mathematical modelling has improved the mechanistic understanding of stem cell dynamics in the adult brain. We also discuss how single-cell sequencing has influenced the understanding of cell states or cell types. Finally, we discuss how the combination of single-cell sequencing technologies and mathematical modelling provides a unique opportunity to answer some burning questions in the field of stem cell biology.

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神经干细胞的数学:连接数据和过程
成体干细胞被描述为一个离散的细胞群体,它位于逐渐分化的细胞层次的顶部。通过其独特的自我更新和分化能力,它们调节有助于组织生理的末端分化细胞的数量。通过这些层次结构的转变是如何离散、连续或可逆的,以及决定干细胞成年后最终表现的确切参数,是深入研究的主题。在这篇综述中,我们解释了数学建模如何提高对成人大脑中干细胞动力学的机制理解。我们还讨论了单细胞测序如何影响对细胞状态或细胞类型的理解。最后,我们讨论了单细胞测序技术和数学建模的结合如何为回答干细胞生物学领域的一些紧迫问题提供了一个独特的机会。
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来源期刊
Cells and Development
Cells and Development Biochemistry, Genetics and Molecular Biology-Developmental Biology
CiteScore
2.90
自引率
0.00%
发文量
33
审稿时长
41 days
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