Going the distance for protein function prediction: a new distance metric for protein interaction networks

Due to an error introduced in the production process, the x-axes in the first panels of Figure 1 and Figure 7 are not formatted correctly. The correct Figure 1 can be viewed here: http://dx.doi.org/10.1371/annotation/343bf260-f6ff-48a2-93b2-3cc79af518a9In protein-protein interaction (PPI) networks, functional similarity is often inferred based on the function of directly interacting proteins, or more generally, some notion of interaction network proximity among proteins in a local neighborhood. Prior methods typically measure proximity as the shortest-path distance in the network, but this has only a limited ability to capture fine-grained neighborhood distinctions, because most proteins are close to each other, and there are many ties in proximity. We introduce diffusion state distance (DSD), a new metric based on a graph diffusion property, designed to capture finer-grained distinctions in proximity for transfer of functional annotation in PPI networks. We present a tool that, when input a PPI network, will output the DSD distances between every pair of proteins. We show that replacing the shortest-path metric by DSD improves the performance of classical function prediction methods across the board.MC, HZ, NMD and LJC were supported in part by National Institutes of Health (NIH) R01 grant GM080330. JP was supported in part by NIH grant R01 HD058880. This material is based upon work supported by the National Science Foundation under grant numbers CNS-0905565, CNS-1018266, CNS-1012910, and CNS-1117039, and supported by the Army Research Office under grant W911NF-11-1-0227 (to MEC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Numerical computations of two-dimensional solitary waves generated by moving disturbances

Two-dimensional solitary waves generated by disturbances moving near the critical speed in shallow water are computed by a time-stepping procedure combined with a desingularized boundary integral method for irrotational flow. The fully non-linear kinematic and dynamic free-surface boundary conditions and the exact rigid body surface condition are employed. Three types of moving disturbances are considered: a pressure on the free surface, a change in bottom topography and a submerged cylinder. The results for the free surface pressure are compared to the results computed using a lower-dimensional model, i.e. the forced Korteweg–de Vries (fKdV) equation. The fully non-linear model predicts the upstream runaway solitons for all three types of disturbances moving near the critical speed. The predictions agree with those by the fKdV equation for a weak pressure disturbance. For a strong disturbance, the fully non-linear model predicts larger solitons than the fKdV equation. The fully non-linear calculations show that a free surface pressure generates significantly larger waves than that for a bottom bump with an identical non-dimensional forcing function in the fKdV equation. These waves can be very steep and break either upstream or downstream of the disturbance.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/50208/1/1650171006_ftp.pd

Generation of 3-Dimensional graph state with Josephson charge qubits

On the basis of generations of 1-dimensional and 2-dimensional graph states, we generate a 3-dimensional N3-qubit graph state based on the Josephson charge qubits. Since any two charge qubits can be selectively and effectively coupled by a common inductance, the controlled phase transform between any two-qubit can be performed. Accordingly, we can generate arbitrary multi-qubit graph states corresponding to arbitrary shape graph, which meet the expectations of various quantum information processing schemes. All the devices in the scheme are well within the current technology. It is a simple, scalable and feasible scheme for the generation of various graph states based on the Josephson charge qubits.Comment: 4 pages, 4 figure

A Systematic Review of Social Networks Research in Information Systems: Building a Foundation for Exciting Future Research

Social networking applications such as blogs, instant messengers, podcasts, social networking websites (e.g., Renren in China, Vkontakte in Russia, Facebook), professional networking websites (e.g., LinkedIn), Twitter, and virtual worlds (e.g., Second Life) have become increasingly popular in the last few years. Because these applications have substantial implications for users, organizations, and society, social networks (SNs) have gained attention from information systems (IS) researchers and grown steadily as a research area since 2004. However, to organize the accumulated research and encourage researchers to examine new and pressing issues in SNs, available knowledge needs to be synthesized and research gaps need to be addressed (Bandara et al., 2011). Therefore, we systematically reviewed publications about SNs published in major IS journals between January 2004 and August 2013 and, in this paper, overview the state of IS research regarding SNs. We show the evolution of the existing IS research on SNs to build a common nomenclature and taxonomy for this area of research, to identify theories used, and to provide a useful roadmap for future research in this area

Stratégies d'amélioration génétique du palmier à huile

La sélection du palmier à huile est conduite selon un schéma de sélection récurrente réciproque qui exploite l'hétérosis existant entre deux groupes de populations (A et B). En raison de la faible héritabilité des caractères de production, la sélection est réalisée après des tests sur descendances (A x B). S'agissant d'une plante à cycle long, les phases de recombinaisons intra-groupe ne comportent qu'une ou deux générations. Est-il utile d'ajouter encore une génération en autofécondation ? La discussion prend en compte l'effet de l'autofécondation sur la structure de la variance, la complémentarité des géniteurs recombinés, la gestion du temps, la nécessité d'assurer une sortie variétale régulière. Une stratégie d'ensemble est proposée pour l'amélioration génétique du palmier à huile. (Résumé d'auteur

Dimensional reduction, quantum Hall effect and layer parity in graphite films

The quantum Hall effect (QHE) originates from discrete Landau levels forming in a two-dimensional (2D) electron system in a magnetic field. In three dimensions (3D), the QHE is forbidden because the third dimension spreads Landau levels into multiple overlapping bands, destroying the quantisation. Here we report the QHE in graphite crystals that are up to hundreds of atomic layers thick - thickness at which graphite was believed to behave as a 3D bulk semimetal. We attribute the observation to a dimensional reduction of electron dynamics in high magnetic fields, such that the electron spectrum remains continuous only in the direction of the magnetic field, and only the last two quasi-one-dimensional (1D) Landau bands cross the Fermi level. In sufficiently thin graphite films, the formation of standing waves breaks these 1D bands into a discrete spectrum, giving rise to a multitude of quantum Hall plateaux. Despite a large number of layers, we observe a profound difference between films with even and odd numbers of graphene layers. For odd numbers, the absence of inversion symmetry causes valley polarisation of the standing-wave states within 1D Landau bands. This reduces QHE gaps, as compared to films of similar thicknesses but with even layer numbers because the latter retain the inversion symmetry characteristic of bilayer graphene. High-quality graphite films present a novel QHE system with a parity-controlled valley polarisation and intricate interplay between orbital, spin and valley states, and clear signatures of electron-electron interactions including the fractional QHE below 0.5 K