13953242
New developments in the InterPro database
InterPro is an integrated resource for protein families, domains and functional sites, which integrates the following protein signature databases: PROSITE, PRINTS, ProDom, Pfam, SMART, TIGRFAMs, PIRSF, SUPERFAMILY, Gene3D and PANTHER. The latter two new member databases have been integrated since the last publication in this journal. There have been several new developments in InterPro, including an additional reading field, new database links, extensions to the web interface and additional match XML files. InterPro has always provided matches to UniProtKB proteins on the website and in the match XML file on the FTP site. Additional matches to proteins in UniParc (UniProt archive) are now available for download in the new match XML files only. The latest InterPro release (13.0) contains more than 13 000 entries, covering over 78% of all proteins in UniProtKB. The database is available for text- and sequence-based searches via a webserver (), and for download by anonymous FTP (). The InterProScan search tool is now also available via a web service at .
5414394
Artificial Neural Networks for Molecular Sequence Analysis
Artificial neural networks provide a unique computing architecture whose potential has attracted interest from researchers across different disciplines. As a technique for computational analysis, neural network technology is very well suited for the analysis of molecular sequence data. It has been applied successfully to a variety of problems, ranging from gene identification, to protein structure prediction and sequence classification. This article provides an overview of major neural network paradigms, discusses design issues, and reviews current applications in DNA/RNA and protein sequence analysis.
6603995
Protein family classification and functional annotation
With the accelerated accumulation of genomic sequence data, there is a pressing need to develop computational methods and advanced bioinformatics infrastructure for reliable and large-scale protein annotation and biological knowledge discovery. The Protein Information Resource (PIR) provides an integrated public resource of protein informatics to support genomic and proteomic research. PIR produces the Protein Sequence Database of functionally annotated protein sequences. The annotation problems are addressed by a classification-driven and rule-based method with evidence attribution, coupled with an integrated knowledge base system being developed. The approach allows sensitive identification, consistent and rich annotation, and systematic detection of annotation errors, as well as distinction of experimentally verified and computationally predicted features. The knowledge base consists of two new databases, sequence analysis tools, and graphical interfaces. PIR-NREF, a non-redundant reference database, provides a timely and comprehensive collection of all protein sequences, totaling more than 1,000,000 entries. iProClass, an integrated database of protein family, function, and structure information, provides extensive value-added features for about 830,000 proteins with rich links to over 50 molecular databases. This paper describes our approach to protein functional annotation with case studies and examines common identification errors. It also illustrates that data integration in PIR supports exploration of protein relationships and may reveal protein functional associations beyond sequence homology.
471313
Dependence network modeling for biomarker identification
MOTIVATION
Our purpose is to develop a statistical modeling approach for cancer biomarker discovery and provide new insights into early cancer detection. We propose the concept of dependence network, apply it for identifying cancer biomarkers, and study the difference between the protein or gene samples from cancer and non-cancer subjects based on mass-spectrometry (MS) and microarray data.


RESULTS
Three MS and two gene microarray datasets are studied. Clear differences are observed in the dependence networks for cancer and non-cancer samples. Protein/gene features are examined three at one time through an exhaustive search. Dependence networks are constructed by binding triples identified by the eigenvalue pattern of the dependence model, and are further compared to identify cancer biomarkers. Such dependence-network-based biomarkers show much greater consistency under 10-fold cross-validation than the classification-performance-based biomarkers. Furthermore, the biological relevance of the dependence-network-based biomarkers using microarray data is discussed. The proposed scheme is shown promising for cancer diagnosis and prediction.


AVAILABILITY
See supplements: http://dsplab.eng.umd.edu/~genomics/dependencenetwork/
21872273
The Protein Information Resource (PIR)
The Protein Information Resource (PIR) produces the largest, most comprehensive, annotated protein sequence database in the public domain, the PIR-International Protein Sequence Database, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Sequence Database (JIPID). The expanded PIR WWW site allows sequence similarity and text searching of the Protein Sequence Database and auxiliary databases. Several new web-based search engines combine searches of sequence similarity and database annotation to facilitate the analysis and functional identification of proteins. New capabilities for searching the PIR sequence databases include annotation-sorted search, domain search, combined global and domain search, and interactive text searches. The PIR-International databases and search tools are accessible on the PIR WWW site at http://pir.georgetown.edu and at the MIPS WWW site at http://www. mips.biochem.mpg.de. The PIR-International Protein Sequence Database and other files are also available by FTP.
205231250
The Universal Protein Resource (UniProt)
The ability to store and interconnect all available information on proteins is crucial to modern biological research. Accordingly, the Universal Protein Resource (UniProt) plays an increasingly important role by providing a stable, comprehensive, freely accessible central resource on protein sequences and functional annotation. UniProt is produced by the UniProt Consortium, formed in 2002 by the European Bioinformatics Institute (EBI), the Protein Information Resource (PIR) and the Swiss Institute of Bioinformatics (SIB). The core activities include manual curation of protein sequences assisted by computational analysis, sequence archiving, development of a user-friendly UniProt web site and the provision of additional value-added information through cross-references to other databases. UniProt is comprised of three major components, each optimized for different uses: the UniProt Archive, the UniProt Knowledgebase and the UniProt Reference Clusters. An additional component consisting of metagenomic and environmental sequences has recently been added to UniProt to ensure availability of such sequences in a timely fashion. UniProt is updated and distributed on a bi-weekly basis and can be accessed online for searches or download at .
8015300
MPI programming environment for IBM SP1/SP2
In this paper we discuss an implementation of the message passing interface standard (MPI) for the IBM Scalable Power PARALLEL 1 and 2 (SP1, SP2). Key to a reliable and efficient implementation of a message passing library on these machines is the careful design of a UNIX-Socket like layer in the user space with controlled access to the communication adapters and with adequate recovery and flow control. The performance of this implementation is at the same level as the IBM-proprietary message passing library (MPL). We also show that in the IBM SP1 and SP2 we achieve integrated tracing ability, where both system events, such as context switches and page fault etc., and MPI related activities are traced, with minimal overhead to the application program, thus presenting application programmers the trace of all the events that ultimately affect efficiency of a parallel program.
15213655
The design and implementation of intelligent transportation Web services
The paper presents the design and implementation of an intelligent transportation Web service (ITWS) and studies various QoS requirements for the Web service infrastructure. In particular, we pay attention to the performance issues on ITWS data transmission and compression. Since SOAP message is a textual document, we can improve the data transmission time by compressing data on transmission. In our experiment, compressing data before or after SOAP serialization both can reduce the size of transmitted message down to as little as 2% and cut the response time to a quarter of the original message.
6100465
A distributed connection manager interface for web services on IBM SP systems
In essence, the World Wide Web is a worldwide string of computer databases using a common information retrieval architecture. With the increasing popularity of the World Wide Web, more and more functions have been added to retrieve not only documents written in HTML (Hypertext Markup Language), but also those in other forms through the Common Gateway Interface (CGI), by constructing HTML documents dynamically. Dynamic construction of HTML documents for handling information such as digital libraries is slow and requires much more computer power. A significant performance bottleneck is the initialization and setup phase for a CGI process to gain access to the system containing the data. In this paper we describe the design and implementation of a Connection Manager Interface on IBM SP systems. The Connection Manager provides cliette processes to serve CGI requests and eliminates such bottlenecks. An IBM SP system is used for this emerging area to show that our design and implementation is flexible enough to take advantage of the High-Performance Switch in an IBM SP system. We trace and monitor this scalable Web services using UTE (Unified Trace Environment) tools, and present its performance analysis and visualization.
490124
Modeling Psychological Refractory Period (PRP) and Practice Effect on PRP with Queuing Networks and Reinforcement Learning Algorithms
PRP (Psychological Refractory Period) is a basic but important form of human information processing in dual-task situations. This article describes a queuing network model of PRP that successfully modeled PRP without the need of setting up complex lock/unlock performance strategies employed in the EPIC model of PRP or drawing complex scheduling charts employed in the ACT-R/PM model of PRP. Further, by integrating queuing networks with reinforcement learning algorithms, the queuing network model successfully simulated practice effect on PRP, which has not been modeled in existing PRP models. The current research indicates that depending on an individual’s degree of practice, cognition can be either serial or parallel at the level of production or response selection. Extensions of queuing network model in modeling other tasks and its easiness in modeling concurrent tasks in practice are also discussed.
42567371
Token Systems that Self-Stabilize
Presents a novel class of mutual exclusion systems, in which processes circulate one token, and each process enters its critical section when it receives the token. Each system in the class is self-stabilizing; i.e. it it starts at any state, possibly one where many tokens exist in the system, it is guaranteed to converge to a good state where exactly one token exists in the system. The systems are better than previous systems in that their state transitions are noninterfering; i.e., if any state transition is enabled at any instant, then it will continue to be enabled until it is executed. This makes the systems easier to implement as delay-insensitive circuits. >