A mathematical model of absorbing Markov chains to understand the routes of metastasis

Autores
Margarit, David Hipólito; Romanelli, Lilia Mabel
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Metastasis is a complex and multi-step stochastic process. The study of the probabilities of generating a tumor from a primary site in another organs is the aim of this work. Based on statistics of National Institute of Cancer of Argentina (INC), a characterization of the routes of metastasis for the principal organs is presented by using Absorbing Markov chains. The metastasis propagation from different primary sites towards secondary and tertiary sites is also shown, emphasizing the relation and analysis about absorbing states.
Fil: Margarit, David Hipólito. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina
Fil: Romanelli, Lilia Mabel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina
Materia
Procesos Markovianos
metastasis
cancer
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:11336/106675
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A mathematical model of absorbing Markov chains to understand the routes of metastasisMargarit, David HipólitoRomanelli, Lilia MabelProcesos Markovianosmetastasiscancerhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Metastasis is a complex and multi-step stochastic process. The study of the probabilities of generating a tumor from a primary site in another organs is the aim of this work. Based on statistics of National Institute of Cancer of Argentina (INC), a characterization of the routes of metastasis for the principal organs is presented by using Absorbing Markov chains. The metastasis propagation from different primary sites towards secondary and tertiary sites is also shown, emphasizing the relation and analysis about absorbing states.Fil: Margarit, David Hipólito. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de General Sarmiento. Instituto de Ciencias; ArgentinaFil: Romanelli, Lilia Mabel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de General Sarmiento. Instituto de Ciencias; ArgentinaUniversidad de Pretoria2016-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/106675Margarit, David Hipólito; Romanelli, Lilia Mabel; A mathematical model of absorbing Markov chains to understand the routes of metastasis; Universidad de Pretoria; Biomtah; 5; 1; 8-2016; 1-101314-684X1314-7218CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.11145/j.biomath.2016.07.281info:eu-repo/semantics/altIdentifier/url/http://www.biomathforum.org/biomath/index.php/biomath/article/view/j.biomath.2016.07.281info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:01:44Zoai:ri.conicet.gov.ar:11336/106675instacron: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:34982025-09-03 10:01:44.754CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A mathematical model of absorbing Markov chains to understand the routes of metastasis
title A mathematical model of absorbing Markov chains to understand the routes of metastasis
spellingShingle A mathematical model of absorbing Markov chains to understand the routes of metastasis
Margarit, David Hipólito
Procesos Markovianos
metastasis
cancer
title_short A mathematical model of absorbing Markov chains to understand the routes of metastasis
title_full A mathematical model of absorbing Markov chains to understand the routes of metastasis
title_fullStr A mathematical model of absorbing Markov chains to understand the routes of metastasis
title_full_unstemmed A mathematical model of absorbing Markov chains to understand the routes of metastasis
title_sort A mathematical model of absorbing Markov chains to understand the routes of metastasis
dc.creator.none.fl_str_mv Margarit, David Hipólito
Romanelli, Lilia Mabel
author Margarit, David Hipólito
author_facet Margarit, David Hipólito
Romanelli, Lilia Mabel
author_role author
author2 Romanelli, Lilia Mabel
author2_role author
dc.subject.none.fl_str_mv Procesos Markovianos
metastasis
cancer
topic Procesos Markovianos
metastasis
cancer
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Metastasis is a complex and multi-step stochastic process. The study of the probabilities of generating a tumor from a primary site in another organs is the aim of this work. Based on statistics of National Institute of Cancer of Argentina (INC), a characterization of the routes of metastasis for the principal organs is presented by using Absorbing Markov chains. The metastasis propagation from different primary sites towards secondary and tertiary sites is also shown, emphasizing the relation and analysis about absorbing states.
Fil: Margarit, David Hipólito. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina
Fil: Romanelli, Lilia Mabel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de General Sarmiento. Instituto de Ciencias; Argentina
description Metastasis is a complex and multi-step stochastic process. The study of the probabilities of generating a tumor from a primary site in another organs is the aim of this work. Based on statistics of National Institute of Cancer of Argentina (INC), a characterization of the routes of metastasis for the principal organs is presented by using Absorbing Markov chains. The metastasis propagation from different primary sites towards secondary and tertiary sites is also shown, emphasizing the relation and analysis about absorbing states.
publishDate 2016
dc.date.none.fl_str_mv 2016-08
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/11336/106675
Margarit, David Hipólito; Romanelli, Lilia Mabel; A mathematical model of absorbing Markov chains to understand the routes of metastasis; Universidad de Pretoria; Biomtah; 5; 1; 8-2016; 1-10
1314-684X
1314-7218
CONICET Digital
CONICET
url http://hdl.handle.net/11336/106675
identifier_str_mv Margarit, David Hipólito; Romanelli, Lilia Mabel; A mathematical model of absorbing Markov chains to understand the routes of metastasis; Universidad de Pretoria; Biomtah; 5; 1; 8-2016; 1-10
1314-684X
1314-7218
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.11145/j.biomath.2016.07.281
info:eu-repo/semantics/altIdentifier/url/http://www.biomathforum.org/biomath/index.php/biomath/article/view/j.biomath.2016.07.281
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
dc.publisher.none.fl_str_mv Universidad de Pretoria
publisher.none.fl_str_mv Universidad de Pretoria
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_ 1842269714780258304
score 13.13397

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