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.complex network | modular organization | self-similarity | stem cells T he cell differentiation process plays a crucial role in the prenatal development of multicellular organisms. Recent advances in the research on stem cell properties and embryonic development have uncovered several steps in the differentiation process (1-7). Single and multiple sequences of cell differentiation have been identified through in vivo observations of a particular embryo during early stages of development and through pathology studies of miscarriages during late stages of the process. While the identification of each cell differentiation step has been the subject of intense research, an integrated view of this complex process is still missing. Such a global view promises to reveal features associated with the large-scale modular organization of the cell types (5-12) with the purpose of discovering functional modules between cell types by using theoretical network analysis for community detection (9-11). In this letter, we take advantage of the current knowledge on the sequence of cell differentiation processes that is spread over a vast specialized literature (1-6, 13-27) (SI Appendix), to reveal and characterize the topological and dynamical features associated with the network of human cell differentiation (NHCD). I. ResultsWe construct the NHCD by systematically gathering the scattered information on the evolution of each cell type present in the embryo and fetus from a predecessor with a higher degree of differentiation potential into a more specialized type. The process of cell differentiation is then mapped onto a complex network that consists of 873...
The source code of our software is available online at www.vivas.ufba.br/bone/bone.zip .br Supplementaty information: Supplementary data are available at Bioinformatics online.
O biogás é um importante tipo de biocombustível obtido a partir de fontes de energia renováveis. Ele pode ser produzido a partir de resíduos urbanos ou industriais e também por decomposição de resíduos orgânicos ou animais. Por esta razão, a quantidade de pesquisas e publicações sobre biogás teve um rápido crescimento nas últimas décadas. Além disso, o número de artigos escritos em coautoria aumentou significativamente. Desta forma, este trabalho construiu a rede de colaboração científica sobre o biogás em um período de 65 anos, ou seja, 1945-2010. Os documentos foram recuperados a partir da base de dados do Web of Knowledge do Institute for Scientific Information (ISI). As consultas foram feitas buscando-se o nome biogás no título do artigo. Assim, três redes foram construídas: autores, instituições e países. No período estudado, foram analisados 1238 trabalhos. Estes documentos foram publicados por 2852 autores diferentes em 1000 instituições distintas pertencentes a 89 países. Os cinco principais países foram a Índia, Alemanha, Estados Unidos da América, China e Dinamarca, respectivamente. Uma observação interessante é que cerca de 85% das publicações tinham pelo menos um tipo de coautoria entre autores, instituições ou países.
RESUMO Redes de colaboração científica representam estratégias para compartilhamento de informações e novos conhecimentos sobre as comunidades acadêmicas. Este tipo de rede pode identificar os agentes que compõem a rede e a intensidade da ligação que une os atores. Por esta razão, neste trabalho foram identificadas as relações entre os autores, países e instituições em publicações sobre seis oleaginosas pertencentes à cadeia produtiva do biodiesel. As oleaginosas selecionados foram soja, pinhão-manso, dendê, canola, girassol e mamona. Nesta rede, os vértices são autores, países ou instituições e as arestas são obtidas por meio da análise publicação. Portanto, se dois cientistas são coautores em uma publicação, eles estão conectados. As publicações sobre estas seis oleaginosas foram recuperadas da base de dados do Web of Knowledge de 1945 a 2011. As consultas foram feitas no modo de Pesquisa Avançada, procurando o nome da oleaginosa no título da publicação e a palavra biodiesel no título, resumo ou palavras-chave. Para cada oleaginosa, três redes foram construídas: autores, países e instituições. No período estudado, foram analisados um total de 1378 publicações. Quatro países (Brasil, Índia, China e Estados Unidos da América) participaram das publicações sobre todas as oleaginosas estudadas.
Abstract. The World Health Organization considers leishmaniasis as one of the six most important tropical diseases in the world. Actually, it is endemic in 88 countries and the different types of this disease affects approximately 12 million of people worldwide. Leishmaniasis is caused by protozoan parasites of the genus Leishmania. The mechanisms of the cellular response against leishmaniasis are not completely known. Additionally, there is still a lack of understanding on the metabolism of the parasite. In this way, we have developed and analyzed a computational model for the immune response to Leishmania major infection by using multi-agent systems. In our model, we have seven different cell types: Leishmania major, CD4-T cell (resting and activated), macrophage (resting, activated, infected, chronically infected), eosinophil (resting and activated), neutrophil, dendritic cell (resting and activated), and keratinocyte. Furthermore, there are void sites to simulate the mobility of the cells. Our model can simulate migration, activation, phagocytosis, and cellular death by lifetime. It was constructed on a three-dimensional cubic lattice. The results show that the kinetics of different cell types does not change for different lattice size. Furthermore, our results suggest that an agent-based approach is a suitable instrument for investigating the cellular interaction. Keywords.multi-agent, leishmaniasis, computational model, immune response, protozoan infection 1 vivgalvao@gmail.com 2
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.