Por favor, use este identificador para citar o enlazar este ítem: https://repositorio.ufba.br/handle/ri/13922
metadata.dc.type: Artigo de Periódico
Título : Modularity map of the network of human cell differentiation
Otros títulos : Proceedings of the National Academy of Sciences
Autor : Galvão, Viviane
Miranda, José Garcia Vivas
Andrade, Roberto Fernandes Silva
Andrade Júnior, José Soares de
Gallos, Lazaros K.
Makse, Hernán A.
metadata.dc.creator: Galvão, Viviane
Miranda, José Garcia Vivas
Andrade, Roberto Fernandes Silva
Andrade Júnior, José Soares de
Gallos, Lazaros K.
Makse, Hernán A.
Resumen : Cell differentiation in multicellular organisms is a complex process whose mechanism can be understood by a reductionist approach, in which the individual processes that control the generation of different cell types are identified. Alternatively, a large-scale approach in search of different organizational features of the growth stages promises to reveal its modular global structure with the goal of discovering previously unknown relations between cell types. Here, we sort and analyze a large set of scattered data to construct the network of human cell differentiation (NHCD) based on cell types (nodes) and differentiation steps (links) from the fertilized egg to a developed human. We discover a dynamical law of critical branching that reveals a self-similar regularity in the modular organization of the network, and allows us to observe the network at different scales. The emerging picture clearly identifies clusters of cell types following a hierarchical organization, ranging from sub-modules to super-modules of specialized tissues and organs on varying scales. This discovery will allow one to treat the development of a particular cell function in the context of the complex network of human development as a whole. Our results point to an integrated large-scale view of the network of cell types systematically revealing ties between previously unrelated domains in organ functions.
Palabras clave : Complex network
Modular organization
Self-similarity
Stem cells
metadata.dc.rights: Acesso Aberto
URI : http://repositorio.ufba.br/ri/handle/ri/13922
Fecha de publicación : 2010
Aparece en las colecciones: Artigo Publicado em Periódico (FIS)

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