Generation and robustness of Boolean networks to model Clostridium difficile infection
Author
dc.contributor.author
Travisany, Dante
Author
dc.contributor.author
Goles, Eric
Author
dc.contributor.author
Latorre, Mauricio
Author
dc.contributor.author
Cortés, María Paz
Author
dc.contributor.author
Maass Sepúlveda, Alejandro
Admission date
dc.date.accessioned
2019-10-15T12:25:21Z
Available date
dc.date.available
2019-10-15T12:25:21Z
Publication date
dc.date.issued
2020
Identifier
dc.identifier.issn
15729796
Identifier
dc.identifier.issn
15677818
Identifier
dc.identifier.other
10.1007/s11047-019-09730-0
Identifier
dc.identifier.uri
https://repositorio.uchile.cl/handle/2250/171660
Abstract
dc.description.abstract
One of the more common healthcare associated infection is Chronic diarrhea. This disease is caused by the bacterium Clostridium difficile which alters the normal composition of the human gut flora. The most successful therapy against this infection is the fecal microbial transplant (FMT). They displace C. difficile and contribute to gut microbiome resilience, stability and prevent further episodes of diarrhea. The microorganisms in the FMT their interactions and inner dynamics reshape the gut microbiome to a healthy state. Even though microbial interactions play a key role in the development of the disease, currently, little is known about their dynamics and properties. In this context, a Boolean network model for C. difficile infection (CDI) describing one set of possible interactions was recently presented. To further explore the space of possible microbial interactions, we propose the construction of a neutral space conformed by a set of models that diff