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Descripción
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| The interaction network became a cornerstone of systems biology. Computer generated models of such networks help to (1) systematically analyze cellular components and pathways, (2) handle the vast amounts of biological data and (3) reveal unanticipated interactions between cellular components and pathways. Biological networks, such as protein-protein interaction networks or gene co-expression networks are examples of scale-free networks, in which some nodes have higher number of connections than others. Thus, a node degree is an analytical measure of local importance of a node in the network. Similarly, the betweenness centrality value is a useful measure of a global node importance and also of the amount of traffic a node has to handle in a network. The importance of nodes with high connectivity and betweenness centrality measures was recently confirmed in biological networks (Li et al., 2011; Lim et al., 2011). Network theory approaches in systems biology allow for data-driven hypothesis construction and gene prioritization. Here we present a functional analysis of nodes/genes with high betweenness centrality measures in plant endomembrane system networks. We hypothesized that altering their expression by means of reverse genetics might result in biological network disturbance and observable phenotypes. | |
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Internacional
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No |
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Nombre congreso
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15th European Plant Endomembrane Research Meeting |
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Tipo de participación
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960 |
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Lugar del congreso
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Madrid |
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Revisores
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No |
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ISBN o ISSN
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0000-0000 |
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DOI
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Fecha inicio congreso
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29/08/2012 |
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Fecha fin congreso
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31/08/2012 |
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Desde la página
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0 |
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Hasta la página
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0 |
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Título de las actas
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Libro de resúmenes del congreso |