A simple physical model for scaling in protein-protein interaction networks

It has recently been demonstrated that many biological networks exhibit a scale-free topology where the probability of observing a node with a certain number of edges (k) follows a power law: i.e. p(k) ~ k^-g. This observation has been reproduced by evolutionary models. Here we consider the network of protein-protein interactions and demonstrate that two published independent measurements of these interactions produce graphs that are only weakly correlated with one another despite their strikingly similar topology. We then propose a physical model based on the fundamental principle that (de)solvation is a major physical factor in protein-protein interactions. This model reproduces not only the scale-free nature of such graphs but also a number of higher-order correlations in these networks. A key support of the model is provided by the discovery of a significant correlation between number of interactions made by a protein and the fraction of hydrophobic residues on its surface. The model presented in this paper represents the first physical model for experimentally determined protein-protein interactions that comprehensively reproduces the topological features of interaction networks. These results have profound implications for understanding not only protein-protein interactions but also other types of scale-free networks.Comment: 50 pages, 17 figure

Quasistatic Scale-free Networks

A network is formed using the $N$ sites of an one-dimensional lattice in the shape of a ring as nodes and each node with the initial degree $k_{in}=2$. $N$ links are then introduced to this network, each link starts from a distinct node, the other end being connected to any other node with degree $k$ randomly selected with an attachment probability proportional to $k^{\alpha}$. Tuning the control parameter $\alpha$ we observe a transition where the average degree of the largest node $$ changes its variation from $N^0$ to $N$ at a specific transition point of $\alpha_c$. The network is scale-free i.e., the nodal degree distribution has a power law decay for $\alpha \ge \alpha_c$.Comment: 4 pages, 5 figure

Self-similar disk packings as model spatial scale-free networks

The network of contacts in space-filling disk packings, such as the Apollonian packing, are examined. These networks provide an interesting example of spatial scale-free networks, where the topology reflects the broad distribution of disk areas. A wide variety of topological and spatial properties of these systems are characterized. Their potential as models for networks of connected minima on energy landscapes is discussed.Comment: 13 pages, 12 figures; some bugs fixed and further discussion of higher-dimensional packing

WormBase 2007

WormBase (www.wormbase.org) is the major publicly available database of information about Caenorhabditis elegans, an important system for basic biological and biomedical research. Derived from the initial ACeDB database of C. elegans genetic and sequence information, WormBase now includes the genomic, anatomical and functional information about C. elegans, other Caenorhabditis species and other nematodes. As such, it is a crucial resource not only for C. elegans biologists but the larger biomedical and bioinformatics communities. Coverage of core areas of C. elegans biology will allow the biomedical community to make full use of the results of intensive molecular genetic analysis and functional genomic studies of this organism. Improved search and display tools, wider cross-species comparisons and extended ontologies are some of the features that will help scientists extend their research and take advantage of other nematode species genome sequences

Directly e-mailing authors of newly published papers encourages community curation

Much of the data within Model Organism Databases (MODs) comes from manual curation of the primary research literature. Given limited funding and an increasing density of published material, a significant challenge facing all MODs is how to efficiently and effectively prioritize the most relevant research papers for detailed curation. Here, we report recent improvements to the triaging process used by FlyBase. We describe an automated method to directly e-mail corresponding authors of new papers, requesting that they list the genes studied and indicate (‘flag’) the types of data described in the paper using an online tool. Based on the author-assigned flags, papers are then prioritized for detailed curation and channelled to appropriate curator teams for full data extraction. The overall response rate has been 44% and the flagging of data types by authors is sufficiently accurate for effective prioritization of papers. In summary, we have established a sustainable community curation program, with the result that FlyBase curators now spend less time triaging and can devote more effort to the specialized task of detailed data extraction

A Gene Wiki for Community Annotation of Gene Function

This manuscript describes the creation of comprehensive gene wiki, seeded with data from public domain sources, which will enable and encourage community annotation of gene function

Search for a dark vector gauge boson decaying to π+π−\pi^+ \pi^- using η→π+π−γ\eta \rightarrow \pi^+\pi^- \gamma decays

We report a search for a dark vector gauge boson $U^\prime$ that couples to quarks in the decay chain $D^{*+} \to D^0 \pi^+, D^0 \to K^0_S \eta, \eta \to U^\prime \gamma$, $U^\prime \to \pi^+ \pi^-$. No signal is found and we set a mass-dependent limit on the baryonic fine structure constant of $10^{-3} - 10^{-2}$ in the $U^\prime$ mass range of 290 to 520 MeV/$c^2$. This analysis is based on a data sample of 976 fb$^{-1}$ collected by the Belle experiment at the KEKB asymmetric-energy $e^+e^-$ collider.Comment: 6 pages, 4 figure

Search for D0D^{0} decays to invisible final states at Belle

We report the result from the first search for $D^0$ decays to invisible final states. The analysis is performed on a data sample of 924 $\rm{fb}^{-1}$ collected at and near the $\Upsilon(4S)$ and $\Upsilon(5S)$ resonances with the Belle detector at the KEKB asymmetric-energy $e^{+}e^{-}$ collider. The absolute branching fraction is determined using an inclusive $D^0$ sample, obtained by fully reconstructing the rest of the particle system including the other charmed particle. No significant signal yield is observed and an upper limit of $9.4\times 10^{-5}$ is set on the branching fraction of $D^0$ to invisible final states at 90\% confidence level.Comment: 17 pages, 4 figures, submitted to PRD(RC

Statistical mechanics of complex networks

Complex networks describe a wide range of systems in nature and society, much quoted examples including the cell, a network of chemicals linked by chemical reactions, or the Internet, a network of routers and computers connected by physical links. While traditionally these systems were modeled as random graphs, it is increasingly recognized that the topology and evolution of real networks is governed by robust organizing principles. Here we review the recent advances in the field of complex networks, focusing on the statistical mechanics of network topology and dynamics. After reviewing the empirical data that motivated the recent interest in networks, we discuss the main models and analytical tools, covering random graphs, small-world and scale-free networks, as well as the interplay between topology and the network's robustness against failures and attacks.Comment: 54 pages, submitted to Reviews of Modern Physic