A stochastic model of neurogenesis controlled by a single factor

Autores
Barton, Alejandro; Fendrik, Alejandro José; Rotondo, Ernesto Federico
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The researches on cortical neurogenesis reveal that asymmetric division plays a key role in controlling the balance between the self-renewal of stem cells and the beginning of the neural differentiation. In such a process a neural stem cell divides by mitosis, originating a postmitotic neuron and other pluripotent stem cell available for subsequent differentiation events. In addition, studies of cell lineage trees of cultured neural progenitors reveal tree shapes and subtrees recurrent, consistent with a stochastic model of division symmetrical/asymmetrical. These considerations have led us to develop a stochastic model of neurogenesis in order to explore the possibility that this is controlled primarily by a single factor (i.e. the concentration of mNumb in the cell). We contrast the predictions of our model with experimental data and compare it with other models of neurogenesis.
Fil: Barton, Alejandro. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina
Fil: Fendrik, Alejandro José. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina
Fil: Rotondo, Ernesto Federico. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina
Materia
Neural Progenitors
Trees Neural Lineage
P And Q Fractions
Asymmetric Segregation
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/35928
Acceder
id CONICETDig_932d64ce4b23aab2012eb9c8788f2ba5
oai_identifier_str oai:ri.conicet.gov.ar:11336/35928
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A stochastic model of neurogenesis controlled by a single factorBarton, AlejandroFendrik, Alejandro JoséRotondo, Ernesto FedericoNeural ProgenitorsTrees Neural LineageP And Q FractionsAsymmetric Segregationhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1The researches on cortical neurogenesis reveal that asymmetric division plays a key role in controlling the balance between the self-renewal of stem cells and the beginning of the neural differentiation. In such a process a neural stem cell divides by mitosis, originating a postmitotic neuron and other pluripotent stem cell available for subsequent differentiation events. In addition, studies of cell lineage trees of cultured neural progenitors reveal tree shapes and subtrees recurrent, consistent with a stochastic model of division symmetrical/asymmetrical. These considerations have led us to develop a stochastic model of neurogenesis in order to explore the possibility that this is controlled primarily by a single factor (i.e. the concentration of mNumb in the cell). We contrast the predictions of our model with experimental data and compare it with other models of neurogenesis.Fil: Barton, Alejandro. Universidad Nacional de General Sarmiento. Instituto de Ciencias; ArgentinaFil: Fendrik, Alejandro José. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de General Sarmiento. Instituto de Ciencias; ArgentinaFil: Rotondo, Ernesto Federico. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de General Sarmiento. Instituto de Ciencias; ArgentinaAcademic Press Ltd-elsevier Science Ltd2014-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/35928Barton, Alejandro; Fendrik, Alejandro José; Rotondo, Ernesto Federico; A stochastic model of neurogenesis controlled by a single factor; Academic Press Ltd-elsevier Science Ltd; Journal of Theoretical Biology; 355; 8-2014; 77-820022-5193CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.jtbi.2014.03.038info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0022519314001945info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:10:23Zoai:ri.conicet.gov.ar:11336/35928instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-10 13:10:23.521CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A stochastic model of neurogenesis controlled by a single factor
title A stochastic model of neurogenesis controlled by a single factor
spellingShingle A stochastic model of neurogenesis controlled by a single factor
Barton, Alejandro
Neural Progenitors
Trees Neural Lineage
P And Q Fractions
Asymmetric Segregation
title_short A stochastic model of neurogenesis controlled by a single factor
title_full A stochastic model of neurogenesis controlled by a single factor
title_fullStr A stochastic model of neurogenesis controlled by a single factor
title_full_unstemmed A stochastic model of neurogenesis controlled by a single factor
title_sort A stochastic model of neurogenesis controlled by a single factor
dc.creator.none.fl_str_mv Barton, Alejandro
Fendrik, Alejandro José
Rotondo, Ernesto Federico
author Barton, Alejandro
author_facet Barton, Alejandro
Fendrik, Alejandro José
Rotondo, Ernesto Federico
author_role author
author2 Fendrik, Alejandro José
Rotondo, Ernesto Federico
author2_role author
author
dc.subject.none.fl_str_mv Neural Progenitors
Trees Neural Lineage
P And Q Fractions
Asymmetric Segregation
topic Neural Progenitors
Trees Neural Lineage
P And Q Fractions
Asymmetric Segregation
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The researches on cortical neurogenesis reveal that asymmetric division plays a key role in controlling the balance between the self-renewal of stem cells and the beginning of the neural differentiation. In such a process a neural stem cell divides by mitosis, originating a postmitotic neuron and other pluripotent stem cell available for subsequent differentiation events. In addition, studies of cell lineage trees of cultured neural progenitors reveal tree shapes and subtrees recurrent, consistent with a stochastic model of division symmetrical/asymmetrical. These considerations have led us to develop a stochastic model of neurogenesis in order to explore the possibility that this is controlled primarily by a single factor (i.e. the concentration of mNumb in the cell). We contrast the predictions of our model with experimental data and compare it with other models of neurogenesis.
Fil: Barton, Alejandro. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina
Fil: Fendrik, Alejandro José. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina
Fil: Rotondo, Ernesto Federico. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina
description The researches on cortical neurogenesis reveal that asymmetric division plays a key role in controlling the balance between the self-renewal of stem cells and the beginning of the neural differentiation. In such a process a neural stem cell divides by mitosis, originating a postmitotic neuron and other pluripotent stem cell available for subsequent differentiation events. In addition, studies of cell lineage trees of cultured neural progenitors reveal tree shapes and subtrees recurrent, consistent with a stochastic model of division symmetrical/asymmetrical. These considerations have led us to develop a stochastic model of neurogenesis in order to explore the possibility that this is controlled primarily by a single factor (i.e. the concentration of mNumb in the cell). We contrast the predictions of our model with experimental data and compare it with other models of neurogenesis.
publishDate 2014
dc.date.none.fl_str_mv 2014-08
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/35928
Barton, Alejandro; Fendrik, Alejandro José; Rotondo, Ernesto Federico; A stochastic model of neurogenesis controlled by a single factor; Academic Press Ltd-elsevier Science Ltd; Journal of Theoretical Biology; 355; 8-2014; 77-82
0022-5193
CONICET Digital
CONICET
url http://hdl.handle.net/11336/35928
identifier_str_mv Barton, Alejandro; Fendrik, Alejandro José; Rotondo, Ernesto Federico; A stochastic model of neurogenesis controlled by a single factor; Academic Press Ltd-elsevier Science Ltd; Journal of Theoretical Biology; 355; 8-2014; 77-82
0022-5193
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jtbi.2014.03.038
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0022519314001945
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Academic Press Ltd-elsevier Science Ltd
publisher.none.fl_str_mv Academic Press Ltd-elsevier Science Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1842980522006937600
score 12.993085

Publicaciones similares