Mathematics of neural stem cells

• Verfasst von: Danciu, Diana-Patricia [VerfasserIn]
• Verfasst von: Hooli, Jooa [VerfasserIn]
• Verfasst von: Martín-Villalba, Ana [VerfasserIn]
• Verfasst von: Marciniak-Czochra, Anna [VerfasserIn]
• Titel: Mathematics of neural stem cells
• Titelzusatz: Linking data and processes
• Verf.angabe: Diana-Patricia Danciu, Jooa Hooli, Ana Martin-Villalba, Anna Marciniak-Czochra
• E-Jahr: 2023
• Jahr: June 2023
• Umfang: 17 S.
• Illustrationen: Illustrationen
• Fussnoten: Online veröffentlicht am 11. Mai 2023 ; Gesehen am 07.12.2023
• Titel Quelle: Enthalten in: Cells & development
• Ort Quelle: Amsterdam : Elsevier, 2021
• Jahr Quelle: 2023
• Band/Heft Quelle: 174(2023) vom: Juni, Artikel-ID 203849, Seite 1-17
• ISSN Quelle: 2667-2901
• DOI: doi:10.1016/j.cdev.2023.203849
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Mechanistic models
• Sach-SW: Neurogenesis
• Sach-SW: Population models
• Sach-SW: Single-cell data
• Sach-SW: Stem cells
• K10plus-PPN: 1852776285

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.