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Hybrid mathematical modeling decodes the complexity of sphingolipid pathway to predict chemosensitivity

dc.creatorMolina Mora, José Arturo
dc.creatorQuirós Barrantes, Steve
dc.creatorKop Montero, Mariana
dc.creatorMora Rodríguez, Rodrigo Antonio
dc.creatorCrespo Mariño, Juan Luis
dc.date.accessioned2022-03-02T13:59:53Z
dc.date.available2022-03-02T13:59:53Z
dc.date.issued2017
dc.descriptionForma parte de los trabajos presentado en el International Conference and Workshop on Bioinspired Intelligence (IWOBI). IEEE, Estados Unidos. Julio de 2017.es_ES
dc.description.abstractSphingolipid (SL) signaling pathway is a complex biological system able to integrate different types of cellular stress signals related to induction of cell death pathways with special interest in cancer. This makes of the SL pathway a promising sensor of chemosensitivity and a target hub to overcome resistance. However, it is unclear how chemotherapeutic drugs can disturb the SL pathway and how the SL content modulates cellular fate. A hybrid mathematical model was proposed in order to integrate i) the metabolism of SL analogue (SM-BODIPY) modeled by an ordinary differential equation (ODE) approach, ii) a Gaussian mixture model (GMM) of the fluorescence features to identify how the SL pathway senses the effect of chemotherapeutic drugs and iii) a fuzzy logic model (FLM) to associate SL composition with cell viability by semi-quantitative rules. Altogether, this hybrid model approach was able to predict the cell viability of double experimental perturbations with chemotherapy, indicating that the SL pathway is a promising sensor to design strategies to overcome drug resistance in cancer.es_ES
dc.description.procedenceUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias de la Salud::Centro de Investigación en Enfermedades Tropicales (CIET)es_ES
dc.description.procedenceUCR::Vicerrectoría de Docencia::Salud::Facultad de Microbiologíaes_ES
dc.identifier.citationhttps://ieeexplore.ieee.org/document/7985532es_ES
dc.identifier.doi10.1109/IWOBI.2017.7985532
dc.identifier.urihttps://hdl.handle.net/10669/85939
dc.language.isoenges_ES
dc.rightsacceso embargado
dc.source2017 International Conference and Workshop on Bioinspired Intelligence (IWOBI). IEEE Xplore, pp.80-85.es_ES
dc.subjectFuzzy logices_ES
dc.subjectCanceres_ES
dc.subjectGMMes_ES
dc.subjectEDOes_ES
dc.subjectSphingolipidses_ES
dc.titleHybrid mathematical modeling decodes the complexity of sphingolipid pathway to predict chemosensitivityes_ES
dc.typecomunicación de congresoes_ES

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