32941506
GeneFIND web server for protein family identification and information retrieval
UNLABELLED
An integrated database and search system has been developed for protein family identification and information retrieval, as an approach to undertake the highly complex, genomic-scale problem of molecular sequence database search and organization.


AVAILABILITY
http://diana.uthct.edu


CONTACT
wu@uthct.edu
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 .
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.
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/
11048111
Modified Chinese remainder theorem and its application to proxy signatures
Chinese Remainder Theorem has been used for hundreds of years and has been applied to many domains such as integers and polynomials. An assumption made is that the component moduli are pairwise co-prime. In this paper, first we remove this assumption; then we give an algorithm to find whether a given system of congruent equations has a solution, and if so, how to find the solution in an efficient manner. Further we apply the modified Chinese Remainder Theorem to design proxy signatures.
40872599
Timestamp consistency and trace-driven analysis for distributed parallel systems
A continuous stream of event data describing the progress of parallel program execution is realized for trace-driven analysis. Unfortunately, it is often the case that separate streams are produced independently by multiple processors in the system, and the logical order of events cannot be guaranteed due to discrepancy among local clocks. We present an integrated approach for timestamp consistency and performance analysis techniques for IBM SPn systems. The trace facility requires no source code modification, and can generate message passing and system events with minimal trace overhead. Trace-driven analysis tools are developed to extract useful information. Analysis results for NAS kernel benchmarks are reported.<<ETX>>
14149213
Efficient Stack Simulation for Shared Memory Set-Associative Multiprocessor Caches
We propose efficient stack simulation algorithms for shared memory multiprocessor (MP) caches. A stack simulation algorithm for write-updated MP caches is first presented. It produces the number of write-updates as well as misses for all cache configurations in a single run. We then devise a new stack simulation algorithm for writeinvalidate MP caches. Our algorithm takes into account cross-invalidation among processors, and generates the number of invalidations as well as misses for all cache configurations in a single run. A cache simulator based on our algorithms for MP caches is developed and the results on sample traces are reported. Our results show that effi cient stack simulation is a powerful technique for multi processor cache analysis.
27793990
Fail Safe Distributed Fault Diagnosis of Multiprocessor Systems
11414897
Trace-based analysis and tuning for distributed parallel applications
We present an integrated approach to deal with timestamp consistency, and trace based performance analysis techniques for distributed parallel applications. Our trace generation facility captures message passing and system events such as process dispatch with minimal trace overhead. Trace driven analysis tools are developed for post execution analysis, reporting information such as the time stolen by other processes in each node, and the observed message passing time and local wait time for each message. We then present our techniques to reduce total elapsed times based on observed message passing times and local wait times.