When the optimal is not the best: Parameter estimation in complex biological models

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Background: The vast computational resources that became available during the past decade enabled the development and simulation of increasingly complex mathematical models of cancer growth. These models typically involve many free parameters whose determination is a substantial obstacle to model de...

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Detalles Bibliográficos
Autores principales: Fernández Slezak, D., Suárez, C., Cecchi, G.A., Marshall, G., Stolovitzky, G.
Formato: Artículo publishedVersion
Publicado: 2010
Materias:
article
bioinformatics
mathematical model
mathematical parameters
process optimization
tumor growth
Cell Division
Humans
Models, Biological
Neoplasms
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_19326203_v5_n10_p_FernandezSlezak
https://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=artiaex&d=paper_19326203_v5_n10_p_FernandezSlezak_oai
Aporte de:
Repositorio Digital de la Universidad de Buenos Aires (UBA) de Universidad de Buenos Aires

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