6933069
Cluestr: mobile social networking for enhanced group communication
Recent technological advances foster the spreading of social software in the mobile domain. Hence, future usage patterns of mobile devices will involve more group interaction. While collaboration using mobile devices is an active area of research, only limited attention has been paid to the efficient initiation of group communication from mobile terminals. In this paper we present a community-aware mechanism that allows to efficiently select contacts in order to address them as a group. We have integrated the proposed method into a proof-of-concept application, and present preliminary experiments that demonstrate the accuracy of the approach and show significant time savings in the group initialization process.
8826212
Distributed asymmetric verification in computational grids
Lucrative incentives in grid computing do not only attract honest participants, but also cheaters. To prevent selfish behavior, verification mechanisms are required. Today's solutions mostly base on redundancy and inherently exhibit a considerable overhead. Often, however, the verification of a result takes much less time than its computation. In this paper we propose a distributed checking scheme that exploits this asymmetry. Our mechanism detects wrong results and excludes cheaters in a distributed manner and hence disburdens the central of the grid server. We show how the verification scheme is used in an application which aims at breaking the discrete logarithm problem by a parallel implementation of the Pollard-p algorithm. Our implementation extends the BOINC server software and is robust to various rational attacks even in the presence of colluders.
1423342
VENETA: Serverless Friend-of-Friend Detection in Mobile Social Networking
Recently, mobile social software has become an active area of research and development. A multitude of systems have been proposed over the past years that try to follow the success of their Internet bound equivalents. Many mobile solutions try to augment the functionality of existing platforms with location awareness. The price for mobility, however, is typically either the lack of the popular friendship exploration features or the costs involved to access a central server required for this functionality. In this paper, we try to address this issue by introducing a decentralized method that is able to explore the social neighborhood of a user by detecting friends of friends. Rather than only exploiting information about the users of the system, the method relies on real friends, and adequately addresses the arising privacy issues. Moreover, we present VENETA, a mobile social networking platform which, among other features, implements our novel friend of friend detection algorithm.
18262140
Dynamic file system semantics to enable metadata optimizations in PVFS
Modern file systems maintain extensive metadata about stored files. While metadata typically is useful, there are situations when the additional overhead of such a design becomes a problem in terms of performance. This is especially true for parallel and cluster file systems, where every metadata operation is even more expensive due to their architecture. In this paper several changes made to the parallel cluster file system Parallel Virtual File System (PVFS) are presented. The changes target at the optimization of workloads with large numbers of small files. To improve the metadata performance, PVFS was modified such that unnecessary metadata is not managed anymore. Several tests with a large quantity of files were performed to measure the benefits of these changes. The tests have shown that common file system operations can be sped up by a factor of two even with relatively few changes. Copyright © 2009 John Wiley & Sons, Ltd.
6311275
STRING 8—a global view on proteins and their functional interactions in 630 organisms
Functional partnerships between proteins are at the core of complex cellular phenotypes, and the networks formed by interacting proteins provide researchers with crucial scaffolds for modeling, data reduction and annotation. STRING is a database and web resource dedicated to protein–protein interactions, including both physical and functional interactions. It weights and integrates information from numerous sources, including experimental repositories, computational prediction methods and public text collections, thus acting as a meta-database that maps all interaction evidence onto a common set of genomes and proteins. The most important new developments in STRING 8 over previous releases include a URL-based programming interface, which can be used to query STRING from other resources, improved interaction prediction via genomic neighborhood in prokaryotes, and the inclusion of protein structures. Version 8.0 of STRING covers about 2.5 million proteins from 630 organisms, providing the most comprehensive view on protein–protein interactions currently available. STRING can be reached at http://string-db.org/.
2031555
OnTheFly: a tool for automated document-based text annotation, data linking and network generation
OnTheFly is a web-based application that applies biological named entity recognition to enrich Microsoft Office, PDF and plain text documents. The input files are converted into the HTML format and then sent to the Reflect tagging server, which highlights biological entity names like genes, proteins and chemicals, and attaches to them JavaScript code to invoke a summary pop-up window. The window provides an overview of relevant information about the entity, such as a protein description, the domain composition, a link to the 3D structure and links to other relevant online resources. OnTheFly is also able to extract the bioentities mentioned in a set of files and to produce a graphical representation of the networks of the known and predicted associations of these entities by retrieving the information from the STITCH database. Availability: http://onthefly.embl.de, http://onthefly.embl.de/FAQ.html Contact: pavlopou@embl.de Supplementary information: Supplementary data are available at Bioinformatics online.
7864638
SuperTarget and Matador: resources for exploring drug-target relationships
The molecular basis of drug action is often not well understood. This is partly because the very abundant and diverse information generated in the past decades on drugs is hidden in millions of medical articles or textbooks. Therefore, we developed a one-stop data warehouse, SuperTarget that integrates drug-related information about medical indication areas, adverse drug effects, drug metabolization, pathways and Gene Ontology terms of the target proteins. An easy-to-use query interface enables the user to pose complex queries, for example to find drugs that target a certain pathway, interacting drugs that are metabolized by the same cytochrome P450 or drugs that target the same protein but are metabolized by different enzymes. Furthermore, we provide tools for 2D drug screening and sequence comparison of the targets. The database contains more than 2500 target proteins, which are annotated with about 7300 relations to 1500 drugs; the vast majority of entries have pointers to the respective literature source. A subset of these drugs has been annotated with additional binding information and indirect interactions and is available as a separate resource called Matador. SuperTarget and Matador are available at http://insilico.charite.de/supertarget and http://matador.embl.de