The Pathosystems Resource Integration Center (PATRIC, www.patricbrc.org) is designed to provide researchers with the tools and services that they need to perform genomic and other 'omic' data analyses. In response to mounting concern over antimicrobial resistance (AMR), the PATRIC team has been developing new tools that help researchers understand AMR and its genetic determinants. To support comparative analyses, we have added AMR phenotype data to over 15 000 genomes in the PATRIC database, often assembling genomes from reads in public archives and collecting their associated AMR panel data from the literature to augment the collection. We have also been using this collection of AMR metadata to build machine learning-based classifiers that can predict the AMR phenotypes and the genomic regions associated with resistance for genomes being submitted to the annotation service. Likewise, we have undertaken a large AMR protein annotation effort by manually curating data from the literature and public repositories. This collection of 7370 AMR reference proteins, which contains many protein annotations (functional roles) that are unique to PATRIC and RAST, has been manually curated so that it projects stably across genomes. The collection currently projects to 1 610 744 proteins in the PATRIC database. Finally, the PATRIC Web site has been expanded to enable AMR-based custom page views so that researchers can easily explore AMR data and design experiments based on whole genomes or individual genes.

Abstract Summary: Annotation of metagenomes involves comparing the individual sequence reads with a database of known sequences and assigning a unique function to each read. This is a time-consuming task that is computationally intensive (though not computationally complex). Here we present a novel approach to annotate metagenomes using unique k-mer oligopeptide sequences from 7 to 12 amino acids long. We demonstrate that k-mer-based annotations are faster and approach the sensitivity and precision of blastx-based annotations without loosing accuracy. A last-common ancestor approach was also developed to describe the members of the community. Availability and implementation: This open-source application was implemented in Perl and can be accessed via a user-friendly website at http://edwards.sdsu.edu/rtmg. In addition, code to access the annotation servers is available for download from http://www.theseed.org/. FIGfams and k-mers are available for download from ftp://ftp.theseed.org/FIGfams/. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

BACKGROUND: The SEED integrates many publicly available genome sequences into a single resource. The database contains accurate and up-to-date annotations based on the subsystems concept that leverages clustering between genomes and other clues to accurately and efficiently annotate microbial genomes. The backend is used as the foundation for many genome annotation tools, such as the Rapid Annotation using Subsystems Technology (RAST) server for whole genome annotation, the metagenomics RAST server for random community genome annotations, and the annotation clearinghouse for exchanging annotations from different resources. In addition to a web user interface, the SEED also provides Web services based API for programmatic access to the data in the SEED, allowing the development of third-party tools and mash-ups. RESULTS: The currently exposed Web services encompass over forty different methods for accessing data related to microbial genome annotations. The Web services provide comprehensive access to the database back end, allowing any programmer access to the most consistent and accurate genome annotations available. The Web services are deployed using a platform independent service-oriented approach that allows the user to choose the most suitable programming platform for their application. Example code demonstrate that Web services can be used to access the SEED using common bioinformatics programming languages such as Perl, Python, and Java. CONCLUSIONS: We present a novel approach to access the SEED database. Using Web services, a robust API for access to genomics data is provided, without requiring large volume downloads all at once. The API ensures timely access to the most current datasets available, including the new genomes as soon as they come online.

Advanced collaborative computing environments are one of the most important tools for integrating high-performance computers and computations and for interacting with colleagues around the world. However, heterogeneous characteristics such as network transfer rates, computational abilities, and hierarchical systems make the seamless integration of distributed resources a challenge. In this paper, we argue that advanced collaborative computing environments need an infrastructure of network services to support distributed and quality guaranteed multimedia applications. Accordingly, we propose the design of network services for high-performance collaborative computing. We present a collaborative environment network service infrastructure (CENSI) to embed network services into various systems intelligently and elastically. We also discuss three management modules: a three-party matching module (resources, requests, and network services), a module for performance monitoring and evaluation of group communications, and a module for distribution topology analysis

Distributed computing middleware needs to support a wide range of resources, such as diverse software components, various hardware devices, and heterogeneous operating systems and architectures. Current technologies are unable to implement a maintenance-free platform to be compatible with such different computing environments. This situation is presenting an increasing challenge as Grid computing becomes more widespread. The infrastructure of network services (CENSA and CENSI) has been proposed to address this challenge. A seamless Grid computing environment, supported by network services, is composed of various streams such as data, video, audio, and text. We define a mathematical model of capability matching for three-party agreements: requests from users, resources, and network services. Based on the mathematical model, we provide a general approach for capability matching. We also present a new language schema for capability description. As an example, we embed the general matchmaker in the architecture of the access Grid. Several tests of accuracy and performance are discussed.

The Argonne Voyager Multimedia Server is being developed in the Futures Lab of the Mathematics and Computer Science Division at Argonne National Laboratory. As a network based service for recording and playing multimedia streams, it is important that the Voyager system be capable of sustaining certain minimal levels of performance in order for it to be a viable system. In this article, we examine the performance characteristics of the server. As we examine the architecture of the system, we try to determine where bottlenecks lie, show actual vs potential performance, and recommend areas for improvement through custom architectures and system tuning.

With the growing presence of multimedia-enabled systems, we will see an integration of collaborative computing concepts into future scientific and technical workplaces. Desktop teleconferencing is common today, while more complex teleconferencing technology that relies on the availability of multipoint-enabled tools is starting to become available on PCs. A critical problem when using these collaborative tools is archiving multistream, multipoint meetings and making the content available to others. Ideally, one would like the ability to capture, record, play back, index, annotate, and distribute multimedia stream data as easily as we currently handle text or still-image data. The Argonne Voyager project is exploring and developing media server technology needed to provide such a flexible, virtual multipoint recording/playback capability. In this article we describe the motivating requirements, architecture, implementation, operation, performance, and related work.