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.
7026402
Exploring music collections on mobile devices
Ever larger collections of music are stored on mobile devices. The process of managing these repositories therefore becomes increasingly challenging. In this work we propose to use a map of the "world of music" as a data structure for music exploration and retrieval on mobile devices. We present Mobile Music Explorer---a mobile application, which allows users to create playlists by specifying trajectories on the map and to use similarity based search methods to navigate through their personal music collections. Our navigation methods ensure that any part of the collection can quickly be reached, even for a large set of items. Moreover, we show that the map representation is a natural approach to provide efficient and distributed operation.
15956763
STRING 7—recent developments in the integration and prediction of protein interactions
Information on protein–protein interactions is still mostly limited to a small number of model organisms, and originates from a wide variety of experimental and computational techniques. The database and online resource STRING generalizes access to protein interaction data, by integrating known and predicted interactions from a variety of sources. The underlying infrastructure includes a consistent body of completely sequenced genomes and exhaustive orthology classifications, based on which interaction evidence is transferred between organisms. Although primarily developed for protein interaction analysis, the resource has also been successfully applied to comparative genomics, phylogenetics and network studies, which are all facilitated by programmatic access to the database backend and the availability of compact download files. As of release 7, STRING has almost doubled to 373 distinct organisms, and contains more than 1.5 million proteins for which associations have been pre-computed. Novel features include AJAX-based web-navigation, inclusion of additional resources such as BioGRID, and detailed protein domain annotation. STRING is available at
14065275
eggNOG: automated construction and annotation of orthologous groups of genes
The identification of orthologous genes forms the basis for most comparative genomics studies. Existing approaches either lack functional annotation of the identified orthologous groups, hampering the interpretation of subsequent results, or are manually annotated and thus lag behind the rapid sequencing of new genomes. Here we present the eggNOG database (‘evolutionary genealogy of genes: Non-supervised Orthologous Groups’), which contains orthologous groups constructed from Smith–Waterman alignments through identification of reciprocal best matches and triangular linkage clustering. Applying this procedure to 312 bacterial, 26 archaeal and 35 eukaryotic genomes yielded 43 582 course-grained orthologous groups of which 9724 are extended versions of those from the original COG/KOG database. We also constructed more fine-grained groups for selected subsets of organisms, such as the 19 914 mammalian orthologous groups. We automatically annotated our non-supervised orthologous groups with functional descriptions, which were derived by identifying common denominators for the genes based on their individual textual descriptions, annotated functional categories, and predicted protein domains. The orthologous groups in eggNOG contain 1 241 751 genes and provide at least a broad functional description for 77% of them. Users can query the resource for individual genes via a web interface or download the complete set of orthologous groups at http://eggnog.embl.de.
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/.