iProClass: an integrated, comprehensive and annotated protein classification database

The iProClass database is an integrated resource that provides comprehensive family relationships and structural and functional features of proteins, with rich links to various databases. It is extended from ProClass, a protein family database that integrates PIR superfamilies and PROSITE motifs. The iProClass currently consists of more than 200 000 non-redundant PIR and SWISS-PROT proteins organized with more than 28 000 superfamilies, 2600 domains, 1300 motifs, 280 post-translational modification sites and links to more than 30 databases of protein families, structures, functions, genes, genomes, literature and taxonomy. Protein and family summary reports provide rich annotations, including membership information with length, taxonomy and keyword statistics, full family relationships, comprehensive enzyme and PDB cross-references and graphical feature display. The database facilitates classification-driven annotation for protein sequence databases and complete genomes, and supports structural and functional genomic research. The iProClass is implemented in Oracle 8i object-relational system and available for sequence search and report retrieval at http://pir.georgetow n.edu/iproclass/.

The emotif database

The emotif database is a collection of more than 170 000 highly specific and sensitive protein sequence motifs representing conserved biochemical properties and biological functions. These protein motifs are derived from 7697 sequence alignments in the BLOCKS+ database (released on June 23, 2000) and all 8244 protein sequence alignments in the PRINTS database (version 27.0) using the emotif-maker algorithm developed by Nevill-Manning et al. (Nevill-Manning,C.G., Wu,T.D. and Brutlag,D.L. (1998) Proc. Natl Acad. Sci. USA, 95, 5865–5871; Nevill-Manning,C.G., Sethi,K.S., Wu,T.D. and Brutlag,D.L. (1997) ISMB-97, 5, 202–209). Since the amino acids and the groups of amino acids in these sequence motifs represent critical positions conserved in evolution, search algorithms employing the emotif patterns can identify and classify more widely divergent sequences than methods based on global sequence similarity. The emotif protein pattern database is available at http://motif.stanford.edu/emotif/.

OrCGDB: a database of genes involved in oral cancer

The Oral Cancer Gene Database (OrCGDB; http://www.tumor-gene.org/Oral/oral.html) was developed to provide the biomedical community with easy access to the latest information on the genes involved in oral cancer. The information is stored in a relational database and accessed through a WWW interface. The OrCGDB is organized by gene name, which is linked to information describing properties of the gene. This information is stored as a collection of findings (‘facts’) that are entered by the database curator in a semi-structured format from information in primary publications using a WWW interface. These facts include causes of oncogenic activation, chromosomal localization of the gene, mutations associated with the gene, the biochemical identity and activity of the gene product, synonyms for the gene name and a variety of clinical information. Each fact is associated with a MEDLINE citation. The user can search the OrCGDB by gene name or by entering a textword. The OrCGDB is part of a larger WWW-based tumor gene database and represents a new approach to catalog and display the research literature.

HyPaLib: a database of RNAs and RNA structural elements defined by hybrid patterns

The database, called HyPaLib (for Hybrid Pattern Library), contains annotated structural elements characteristic for certain classes of structural and/or functional RNAs. These elements are described in a language specifically designed for this purpose. The language allows convenient specification of hybrid patterns, i.e. motifs consisting of sequence features and structural elements together with sequence similarity and thermodynamic constraints. We are currently developing software tools that allow a user to search sequence databases for any pattern in HyPaLib, thus providing functionality which is similar to PROSITE, but dedicated to the more complex patterns in RNA sequences. HyPaLib is available at http://bibiserv.techfak.uni-bielefeld.de/HyPa/.

ParAlign: a parallel sequence alignment algorithm for rapid and sensitive database searches

There is a need for faster and more sensitive algorithms for sequence similarity searching in view of the rapidly increasing amounts of genomic sequence data available. Parallel processing capabilities in the form of the single instruction, multiple data (SIMD) technology are now available in common microprocessors and enable a single microprocessor to perform many operations in parallel. The ParAlign algorithm has been specifically designed to take advantage of this technology. The new algorithm initially exploits parallelism to perform a very rapid computation of the exact optimal ungapped alignment score for all diagonals in the alignment matrix. Then, a novel heuristic is employed to compute an approximate score of a gapped alignment by combining the scores of several diagonals. This approximate score is used to select the most interesting database sequences for a subsequent Smith–Waterman alignment, which is also parallelised. The resulting method represents a substantial improvement compared to existing heuristics. The sensitivity and specificity of ParAlign was found to be as good as Smith–Waterman implementations when the same method for computing the statistical significance of the matches was used. In terms of speed, only the significantly less sensitive NCBI BLAST 2 program was found to outperform the new approach. Online searches are available at http://dna.uio.no/search/

CandiVF - Candida albicans virulence factor database

Candida albicans is a pathogen commonly infecting patients who receive immunosuppressive drug therapy, long-term catheterization, or those who suffer from acquired immune deficiency syndrome (AIDS). The major factor accountable for pathogenicity of C. albicans is host immune status. Various virulence molecules, or factors, of are also responsible for the disease progression. Virulence proteins are published in public databases but they normally lack detailed functional annotations. We have developed CandiVF, a specialized database of C. albicans virulence factors (http://antigen.i2r.a-star.edu.sg/Templar/DB/CandiVF/) to facilitate efficient extraction and analysis of data aimed to assist research on immune responses, pathogenesis, prevention, and control of candidiasis. CandiVF contains a large number of annotated virulence proteins, including secretory, cell wall-associated, membrane, cytoplasmic, and nuclear proteins. This database has in-built bioinformatics tools including keyword and BLAST search, visualization of 3D-structures, HLA-DR epitope prediction, virulence descriptors, and virulence factors ontology.

Searches and content of the OTseeker database: Informing research priorities

BACKGROUND. A strategic and prioritized approach to occupational therapy research is needed, particularly given the limited research funding available. Comparing occupational therapists' information needs with the research evidence available can potentially inform research debate within the profession. This study aimed to identify research topics most often sought by users of the OTseeker database and to compare these with the quantity of topics available in the database. METHOD. A random sample of keyword search terms submitted to OTseeker (n = 4,500) was coded according to diagnostic and intervention categories, and compared with the amount of research contained in OTseeker in 2004. RESULTS. Most frequently sought topics were relevant to the diagnostic categories of pediatric conditions (19%), neurology and neuromuscular disorders (17%), and mental health (17%). Most frequently sought intervention topics included modes of service delivery, sensory interventions, and physical modalities. Although many frequently sought topics had a correspondingly high volume of research in OTseeker, a few areas had very little content (e.g., fine motor skill acquisition, autistic spectrum disorder). This information is offered to inform discussions about research priorities and resource allocation for research within occupational therapy.

SCORPION2: A database for structure-function analysis of scorpion toxins

Scorpion toxins are important experimental tools for characterization of vast array of ion channels and serve as scaffolds for drug design. General public database entries contain limited annotation whereby rich structure-function information from mutation studies is typically not available. SCORPION2 contains more than 800 records of native and mutant toxin sequences enriched with binding affinity and toxicity information, 624 three-dimensional structures and some 500 references. SCORPION2 has a set of search and prediction tools that allow users to extract and perform specific queries: text searches of scorpion toxin records, sequence similarity search, extraction of sequences, visualization of scorpion toxin structures, analysis of toxic activity, and functional annotation of previously uncharacterized scorpion toxins. The SCORPION2 database is available at http://sdmc.i2r.a-star.edu.sg/scorpion/. (c) 2006 Elsevier Ltd. All rights reserved.

Towards effective indexing for very large video sequence database

With rapid advances in video processing technologies and ever fast increments in network bandwidth, the popularity of video content publishing and sharing has made similarity search an indispensable operation to retrieve videos of user interests. The video similarity is usually measured by the percentage of similar frames shared by two video sequences, and each frame is typically represented as a high-dimensional feature vector. Unfortunately, high complexity of video content has posed the following major challenges for fast retrieval: (a) effective and compact video representations, (b) efficient similarity measurements, and (c) efficient indexing on the compact representations. In this paper, we propose a number of methods to achieve fast similarity search for very large video database. First, each video sequence is summarized into a small number of clusters, each of which contains similar frames and is represented by a novel compact model called Video Triplet (ViTri). ViTri models a cluster as a tightly bounded hypersphere described by its position, radius, and density. The ViTri similarity is measured by the volume of intersection between two hyperspheres multiplying the minimal density, i.e., the estimated number of similar frames shared by two clusters. The total number of similar frames is then estimated to derive the overall similarity between two video sequences. Hence the time complexity of video similarity measure can be reduced greatly. To further reduce the number of similarity computations on ViTris, we introduce a new one dimensional transformation technique which rotates and shifts the original axis system using PCA in such a way that the original inter-distance between two high-dimensional vectors can be maximally retained after mapping. An efficient B+-tree is then built on the transformed one dimensional values of ViTris' positions. Such a transformation enables B+-tree to achieve its optimal performance by quickly filtering a large portion of non-similar ViTris. Our extensive experiments on real large video datasets prove the effectiveness of our proposals that outperform existing methods significantly.

Using the Amazon metric to construct an image database based on what people do, not what they say

Current image database metadata schemas require users to adopt a specific text-based vocabulary. Text-based metadata is good for searching but not for browsing. Existing image-based search facilities, on the other hand, are highly specialised and so suffer similar problems. Wexelblat's semantic dimensional spatial visualisation schemas go some way towards addressing this problem by making both searching and browsing more accessible to the user in a single interface. But the question of how and what initial metadata to enter a database remains. Different people see different things in an image and will organise a collection in equally diverse ways. However, we can find some similarity across groups of users regardless of their reasoning. For example, a search on Amazon.com returns other products also, based on an averaging of how users navigate the database. In this paper, we report on applying this concept to a set of images for which we have visualised them using traditional methods and the Amazon.com method. We report on the findings of this comparative investigation in a case study setting involving a group of randomly selected participants. We conclude with the recommendation that in combination, the traditional and averaging methods would provide an enhancement to current database visualisation, searching, and browsing facilities.

Visual search for object orientation can be modulated by canonical orientation

The authors studied the influence of canonical orientation on visual search for object orientation. Displays consisted of pictures of animals whose axis of elongation was either vertical or tilted in their canonical orientation. Target orientation could be either congruent or incongruent with the object's canonical orientation. In Experiment 1, vertical canonical targets were detected faster when they were tilted (incongruent) than when they were vertical (congruent). This search asymmetry was reversed for tilted canonical targets. The effect of canonical orientation was partially preserved when objects were high-pass filtered, but it was eliminated when they were low-pass filtered, rendering them as unfamiliar shapes (Experiment 2). The effect of canonical orientation was also eliminated by inverting the objects (Experiment 3) and in a patient with visual agnosia (Experiment 4). These results indicate that orientation search with familiar objects can be modulated by canonical orientation, and they indicate a top-down influence on orientation processing. (PsycINFO Database Record (c) 2010 APA, all rights reserved)

Communicating Cuneiform:The Evolution of a Multimedia Cuneiform Database

Our paper presents the work of the Cuneiform Digital Forensic Project (CDFP), an interdisciplinary project at The University of Birmingham, concerned with the development of a multimedia database to support scholarly research into cuneiform, wedge-shaped writing imprinted onto clay tablets and indeed the earliest real form of writing. We describe the evolutionary design process and dynamic research and developmental cycles associated with the database. Unlike traditional publications, the electronic publication of resources offers the possibility of almost continuous revisions with the integration and support of new media and interfaces. However, if on-line resources are to win the favor and confidence of their respective communities there must be a clear distinction between published and maintainable resources, and, developmental content. Published material should, ideally, be supported via standard web-browser interfaces with fully integrated tools so that users receive a reliable, homogenous and intuitive flow of information and media relevant to their needs. We discuss the inherent dynamics of the design and publication of our on-line resource, starting with the basic design and maintenance aspects of the electronic database, which includes photographic instances of cuneiform signs, and shows how the continuous review process identifies areas for further research and development, for example, the “sign processor” graphical search tool and three-dimensional content, the results of which then feedback into the maintained resource.

PPD v1.0 - an integrated, web-accessible database of experimentally determined protein pKa values

The Protein pKa Database (PPD) v1.0 provides a compendium of protein residue-specific ionization equilibria (pKa values), as collated from the primary literature, in the form of a web-accessible postgreSQL relational database. Ionizable residues play key roles in the molecular mechanisms that underlie many biological phenomena, including protein folding and enzyme catalysis. The PPD serves as a general protein pKa archive and as a source of data that allows for the development and improvement of pKa prediction systems. The database is accessed through an HTML interface, which offers two fast, efficient search methods: an amino acid-based query and a Basic Local Alignment Search Tool search. Entries also give details of experimental techniques and links to other key databases, such as National Center for Biotechnology Information and the Protein Data Bank, providing the user with considerable background information.

An Algorithm to Mine Normalized Weighted Sequential Patterns Using a Prefix-projected Database

Sequential pattern mining is an important subject in data mining with broad applications in many different areas. However, previous sequential mining algorithms mostly aimed to calculate the number of occurrences (the support) without regard to the degree of importance of different data items. In this paper, we propose to explore the search space of subsequences with normalized weights. We are not only interested in the number of occurrences of the sequences (supports of sequences), but also concerned about importance of sequences (weights). When generating subsequence candidates we use both the support and the weight of the candidates while maintaining the downward closure property of these patterns which allows to accelerate the process of candidate generation.