PhysiBoSS: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling.
Bioinformatics
; 35(7): 1188-1196, 2019 04 01.
Article
en En
| MEDLINE
| ID: mdl-30169736
ABSTRACT
MOTIVATION Due to the complexity and heterogeneity of multicellular biological systems, mathematical models that take into account cell signalling, cell population behaviour and the extracellular environment are particularly helpful. We present PhysiBoSS, an open source software which combines intracellular signalling using Boolean modelling (MaBoSS) and multicellular behaviour using agent-based modelling (PhysiCell). RESULTS:
PhysiBoSS provides a flexible and computationally efficient framework to explore the effect of environmental and genetic alterations of individual cells at the population level, bridging the critical gap from single-cell genotype to single-cell phenotype and emergent multicellular behaviour. PhysiBoSS thus becomes very useful when studying heterogeneous population response to treatment, mutation effects, different modes of invasion or isomorphic morphogenesis events. To concretely illustrate a potential use of PhysiBoSS, we studied heterogeneous cell fate decisions in response to TNF treatment. We explored the effect of different treatments and the behaviour of several resistant mutants. We highlighted the importance of spatial information on the population dynamics by considering the effect of competition for resources like oxygen. AVAILABILITY AND IMPLEMENTATION PhysiBoSS is freely available on GitHub (https//github.com/sysbio-curie/PhysiBoSS), with a Docker image (https//hub.docker.com/r/gletort/physiboss/). It is distributed as open source under the BSD 3-clause license. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Programas Informáticos
/
Transducción de Señal
/
Modelos Genéticos
Tipo de estudio:
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2019
Tipo del documento:
Article
País de afiliación:
Francia