44,184 research outputs found
The architecture of the protein domain universe
Understanding the design of the universe of protein structures may provide
insights into protein evolution. We study the architecture of the protein
domain universe, which has been found to poses peculiar scale-free properties
(Dokholyan et al., Proc. Natl. Acad. Sci. USA 99: 14132-14136 (2002)). We
examine the origin of these scale-free properties of the graph of protein
domain structures (PDUG) and determine that that the PDUG is not modular, i.e.
it does not consist of modules with uniform properties. Instead, we find the
PDUG to be self-similar at all scales. We further characterize the PDUG
architecture by studying the properties of the hub nodes that are responsible
for the scale-free connectivity of the PDUG. We introduce a measure of the
betweenness centrality of protein domains in the PDUG and find a power-law
distribution of the betweenness centrality values. The scale-free distribution
of hubs in the protein universe suggests that a set of specific statistical
mechanics models, such as the self-organized criticality model, can potentially
identify the principal driving forces of molecular evolution. We also find a
gatekeeper protein domain, removal of which partitions the largest cluster into
two large sub-clusters. We suggest that the loss of such gatekeeper protein
domains in the course of evolution is responsible for the creation of new fold
families.Comment: 14 pages, 3 figure
Automated construction and analysis of political networks via open government and media sources
We present a tool to generate real world political networks from user provided lists of politicians and news sites. Additional output includes visualizations, interactive tools and maps that allow a user to better understand the politicians and their surrounding environments as portrayed by the media. As a case study, we construct a comprehensive list of current Texas politicians, select news sites that convey a spectrum of political viewpoints covering Texas politics, and examine the results. We propose a ”Combined” co-occurrence distance metric to better reflect the relationship between two entities. A topic modeling technique is also proposed as a novel, automated way of labeling communities that exist within a politician’s ”extended” network.Peer ReviewedPostprint (author's final draft
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