Phenotypic stability and plasticity in GMP-derived cells as determined by their underlying regulatory network.
| Autor: | Ramírez C; Programa de Doctorado en Ciencias Biomédicas, Universidad Nacional Autónoma de México.; Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Cd. Mx., CP04510, México., Mendoza L; Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Cd. Mx., CP04510, México. |
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| Jazyk: | angličtina |
| Zdroj: | Bioinformatics (Oxford, England) [Bioinformatics] 2018 Apr 01; Vol. 34 (7), pp. 1174-1182. |
| DOI: | 10.1093/bioinformatics/btx736 |
| Abstrakt: | Motivation: Blood cell formation has been recognized as a suitable system to study celular differentiation mainly because of its experimental accessibility, and because it shows characteristics such as hierarchical and gradual bifurcated patterns of commitment, which are present in several developmental processes. Although hematopoiesis has been extensively studied and there is a wealth of molecular and cellular data about it, it is not clear how the underlying molecular regulatory networks define or restrict cellular differentiation processes. Here, we infer the molecular regulatory network that controls the differentiation of a blood cell subpopulation derived from the granulocyte-monocyte precursor (GMP), comprising monocytes, neutrophils, eosinophils, basophils and mast cells. Results: We integrate published qualitative experimental data into a model to describe temporal expression patterns observed in GMP-derived cells. The model is implemented as a Boolean network, and its dynamical behavior is studied. Steady states of the network can be clearly identified with the expression profiles of monocytes, mast cells, neutrophils, basophils, and eosinophils, under wild-type and mutant backgrounds. Availability and Implementation: All scripts are publicly available at https://github.com/caramirezal/RegulatoryNetworkGMPModel. Contact: lmendoza@biomedicas.unam.mx. Supplementary Information: Supplementary data are available at Bioinformatics online. |
| Databáze: | MEDLINE |
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