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PubMed2003

PRECIS: protein reports engineered from concise information in SWISS-PROT.

MOTIVATION: There have been several endeavours to address the problem of annotating sequence data computationally, but the task is non-trivial and few tools have emerged that gather useful information on a given sequence, or set of sequences, in a simple and convenient manner. As more genome projects bear fruit, the mass of uncharacterized sequence data accumulating in public repositories grows ever larger. There is thus a pressing need for tools to support the process of automatic analysis and annotation of newly determined sequences. With this in mind, we have developed PRECIS, which automatically creates protein reports from sets of SWISS-PROT entries, collating results into structured reports, detailing known biological and medical information, literature and database cross-references, and relevant keywords.

Abstracting and Indexing↗

PubMed2003

The UAB Proteomics Database.

SUMMARY: The University of Alabama at Birmingham (UAB) Proteomics Database (UPD) (http://www.uab.edu/proteinmenu) was created to provide a repository for the storage and linkage of two-dimensional (2D) gel images and the associated information obtained through mass spectrometry analysis of the proteins excised from the 2D gels in a manner similar to the SWISS-2DPAGE database and the Stanford Microarray Database. This was accomplished through the development of a web interface, a relational database, image maps and hyperlinks stored in the database. In addition to the internally generated data, UPD provides links to the National Center for Biotechnology Information via accession number hyperlinks. UPD currently contains information on 44 individual proteins derived from four experiments conducted by four UAB faculty members. Images of the gels from which each of these proteins was isolated are accessed by hyperlinks embedded in the database. AVAILABILITY: The UAB Proteomics Database can be accessed at http://www.uab.edu/proteinmenu.

Alabama↗

PubMed2003

The MUSC DNA Microarray Database.

SUMMARY: The Medical University of South Carolina (MUSC) DNA Microarray Database is a web-accessible archive of DNA microarray data. The database was developed using the DNA microarray project/data management system, micro ArrayDB. Annotations for each DNA microarray project and associated cRNA target information are stored in a MySQL relational database and linked to array hybridization data (raw and normalized). At the discretion of investigators, data are placed into the public domain where they can be interrogated and downloaded through a web browser. In addition to serving as an online resource of gene expression data, the MUSC DNA Microarray Database is a model for other academic DNA microarray data repositories. AVAILABILITY: Browsing and downloading of MUSC DNA Microarray Database information can be done after registration at http://proteogenomics.musc.edu/pss/home.php.

Academic Medical Centers↗

PubMed2003

caCORE: a common infrastructure for cancer informatics.

MOTIVATION: Sites with substantive bioinformatics operations are challenged to build data processing and delivery infrastructure that provides reliable access and enables data integration. Locally generated data must be processed and stored such that relationships to external data sources can be presented. Consistency and comparability across data sets requires annotation with controlled vocabularies and, further, metadata standards for data representation. Programmatic access to the processed data should be supported to ensure the maximum possible value is extracted. Confronted with these challenges at the National Cancer Institute Center for Bioinformatics, we decided to develop a robust infrastructure for data management and integration that supports advanced biomedical applications. RESULTS: We have developed an interconnected set of software and services called caCORE. Enterprise Vocabulary Services (EVS) provide controlled vocabulary, dictionary and thesaurus services. The Cancer Data Standards Repository (caDSR) provides a metadata registry for common data elements. Cancer Bioinformatics Infrastructure Objects (caBIO) implements an object-oriented model of the biomedical domain and provides Java, Simple Object Access Protocol and HTTP-XML application programming interfaces. caCORE has been used to develop scientific applications that bring together data from distinct genomic and clinical science sources. AVAILABILITY: caCORE downloads and web interfaces can be accessed from links on the caCORE web site (http://ncicb.nci.nih.gov/core). caBIO software is distributed under an open source license that permits unrestricted academic and commercial use. Vocabulary and metadata content in the EVS and caDSR, respectively, is similarly unrestricted, and is available through web applications and FTP downloads. SUPPLEMENTARY INFORMATION: http://ncicb.nci.nih.gov/core/publications contains links to the caBIO 1.0 class diagram and the caCORE 1.0 Technical Guide, which provide detailed information on the present caCORE architecture, data sources and APIs. Updated information appears on a regular basis on the caCORE web site (http://ncicb.nci.nih.gov/core).

Animals↗

PubMed2003

Accelerating screening of 3D protein data with a graph theoretical approach.

MOTIVATION: The Dictionary of Interfaces in Proteins (DIP) is a database collecting the 3D structure of interacting parts of proteins that are called patches. It serves as a repository, in which patches similar to given query patches can be found. The computation of the similarity of two patches is time consuming and traversing the entire DIP requires some hours. In this work we address the question of how the patches similar to a given query can be identified by scanning only a small part of DIP. The answer to this question requires the investigation of the distribution of the similarity of patches. RESULTS: The score values describing the similarity of two patches can roughly be divided into three ranges that correspond to different levels of spatial similarity. Interestingly, the two iso-score lines separating the three classes can be determined by two different approaches. Applying a concept of the theory of random graphs reveals significant structural properties of the data in DIP. These can be used to accelerate scanning the DIP for patches similar to a given query. Searches for very similar patches could be accelerated by a factor of more than 25. Patches with a medium similarity could be found 10 times faster than by brute-force search.

Algorithms↗

PubMed2003

Automatic discovery and classification of bioinformatics Web sources.

MOTIVATION: The World Wide Web provides an incredible resource to genomics researchers in the form of query access to distributed data sources--e.g. BLAST sequence homology search interfaces. The number of these autonomous sources and their rate of change outpaces the speed at which they can be manually classified, meaning that the available data is not being utilized to its full potential. Manually maintaining a wrapper library will not scale to accommodate the growth of genomics data sources on the Web, challenging us to produce an automated system that can find, classify and wrap new sources without constant human intervention. Previous research has not addressed the problem of automatically locating, classifying and integrating classes of bioinformatics data sources. RESULTS: This paper presents an overview of a system for finding classes of bioinformatics data sources and integrating them behind a unified interface. We describe our approach for automatic classification of new Web sources into relevance categories that eliminates the human effort required to maintain a current repository of sources. Our approach is based on a meta-data description of classes of interesting sources that describes the important features of an entire class of services without tying that description to any particular Web source. We examine the features of this format in the context of BLAST sources to show how it relates to Web sources that are being described. We then show how a description can be used to determine if an arbitrary Web source is an instance of the described service. To validate the effectiveness of this approach, we have constructed a prototype that correctly classifies approximately two-thirds of the BLAST sources we tested. We conclude with a discussion of these results, the factors that affect correct automatic classification and areas for future study.

Algorithms↗

PubMed2004

JDotter: a Java interface to multiple dotplots generated by dotter.

UNLABELLED: Java-Dotter (JDotter) is a platform-independent Java interactive interface for the Linux version of Dotter, a widely used program for generating dotplots of large DNA or protein sequences. JDotter runs as a client-server application and can send new sequences to the Dotter program for alignment as well as rapidly access a repository of preprocessed dotplots. JDotter also interfaces with a sequence database or file system to display supplementary feature data. Thus, JDotter greatly simplifies access to dotplot data in laboratories that deal with large numbers of genomes and have a multi-platform organization. AVAILABILITY: Currently, JDotter is used via Java Web Start by the Poxvirus Bioinformatics Resource for examining dotplots of complete poxvirus genomes; http://athena.bioc.uvic.ca/pbr/jdotter/. The software is available for download from the same location. SUPPLEMENTARY INFORMATION: Installation instructions, the User's Manual, screenshots and examples are available at the JDotter home page http://athena.bioc.uvic.ca/pbr/jdotter/. The software and source code is free for non-commercial applications.

Computer Graphics↗

PubMed2004

Confirmation of data mining based predictions of protein function.

MOTIVATION: A central problem in bioinformatics is the assignment of function to sequenced open reading frames (ORFs). The most common approach is based on inferred homology using a statistically based sequence similarity (SIM) method, e.g. PSI-BLAST. Alternative non-SIM based bioinformatic methods are becoming popular. One such method is Data Mining Prediction (DMP). This is based on combining evidence from amino-acid attributes, predicted structure and phylogenic patterns; and uses a combination of Inductive Logic Programming data mining, and decision trees to produce prediction rules for functional class. DMP predictions are more general than is possible using homology. In 2000/1, DMP was used to make public predictions of the function of 1309 Escherichia coli ORFs. Since then biological knowledge has advanced allowing us to test our predictions. RESULTS: We examined the updated (20.02.02) Riley group genome annotation, and examined the scientific literature for direct experimental derivations of ORF function. Both tests confirmed the DMP predictions. Accuracy varied between rules, and with the detail of prediction, but they were generally significantly better than random. For voting rules, accuracies of 75-100% were obtained. Twenty-one of these DMP predictions have been confirmed by direct experimentation. The DMP rules also have interesting biological explanations. DMP is, to the best of our knowledge, the first non-SIM based prediction method to have been tested directly on new data. AVAILABILITY: We have designed the "Genepredictions" database for protein functional predictions. This is intended to act as an open repository for predictions for any organism and can be accessed at http://www.genepredictions.org

Abstracting and Indexing↗

PubMed2004

An object model and database for functional genomics.

MOTIVATION: Large-scale functional genomics analysis is now feasible and presents significant challenges in data analysis, storage and querying. Data standards are required to enable the development of public data repositories and to improve data sharing. There is an established data format for microarrays (microarray gene expression markup language, MAGE-ML) and a draft standard for proteomics (PEDRo). We believe that all types of functional genomics experiments should be annotated in a consistent manner, and we hope to open up new ways of comparing multiple datasets used in functional genomics. RESULTS: We have created a functional genomics experiment object model (FGE-OM), developed from the microarray model, MAGE-OM and two models for proteomics, PEDRo and our own model (Gla-PSI-Glasgow Proposal for the Proteomics Standards Initiative). FGE-OM comprises three namespaces representing (i) the parts of the model common to all functional genomics experiments; (ii) microarray-specific components; and (iii) proteomics-specific components. We believe that FGE-OM should initiate discussion about the contents and structure of the next version of MAGE and the future of proteomics standards. A prototype database called RNA And Protein Abundance Database (RAPAD), based on FGE-OM, has been implemented and populated with data from microbial pathogenesis. AVAILABILITY: FGE-OM and the RAPAD schema are available from http://www.gusdb.org/fge.html, along with a set of more detailed diagrams. RAPAD can be accessed by registration at the site.

Abstracting and Indexing↗

PubMed2004

CEBS object model for systems biology data, SysBio-OM.

MOTIVATION: To promote a systems biology approach to understanding the biological effects of environmental stressors, the Chemical Effects in Biological Systems (CEBS) knowledge base is being developed to house data from multiple complex data streams in a systems friendly manner that will accommodate extensive querying from users. Unified data representation via a single object model will greatly aid in integrating data storage and management, and facilitate reuse of software to analyze and display data resulting from diverse differential expression or differential profile technologies. Data streams include, but are not limited to, gene expression analysis (transcriptomics), protein expression and protein-protein interaction analysis (proteomics) and changes in low molecular weight metabolite levels (metabolomics). RESULTS: To enable the integration of microarray gene expression, proteomics and metabolomics data in the CEBS system, we designed an object model, Systems Biology Object Model (SysBio-OM). The model is comprehensive and leverages other open source efforts, namely the MicroArray Gene Expression Object Model (MAGE-OM) and the Proteomics Experiment Data Repository (PEDRo) object model. SysBio-OM is designed by extending MAGE-OM to represent protein expression data elements (including those from PEDRo), protein-protein interaction and metabolomics data. SysBio-OM promotes the standardization of data representation and data quality by facilitating the capture of the minimum annotation required for an experiment. Such standardization refines the accuracy of data mining and interpretation. The open source SysBio-OM model, which can be implemented on varied computing platforms is presented here. AVAILABILITY: A universal modeling language depiction of the entire SysBio-OM is available at http://cebs.niehs.nih.gov/SysBioOM/. The Rational Rose object model package is distributed under an open source license that permits unrestricted academic and commercial use and is available at http://cebs.niehs.nih.gov/cebsdownloads. The database and interface are being built to implement the model and will be available for public use at http://cebs.niehs.nih.gov.

Database Management Systems↗

PubMed2004

Web-based kinetic modelling using JWS Online.

UNLABELLED: JWS Online is a repository of kinetic models, describing biological systems, which can be interactively run and interrogated over the Internet. It is implemented using a client-server strategy where the clients, in the form of web browser based Java applets, act as a graphical interface to the model servers, which perform the required numerical computations. AVAILABILITY: The JWS Online website is publicly accessible at http://jjj.biochem.sun.ac.za/ with mirrors at http://www.jjj.bio.vu.nl/ and http://jjj.vbi.vt.edu/

Cell Physiological Phenomena↗

PubMed2004

Taverna: a tool for the composition and enactment of bioinformatics workflows.

MOTIVATION: In silico experiments in bioinformatics involve the co-ordinated use of computational tools and information repositories. A growing number of these resources are being made available with programmatic access in the form of Web services. Bioinformatics scientists will need to orchestrate these Web services in workflows as part of their analyses. RESULTS: The Taverna project has developed a tool for the composition and enactment of bioinformatics workflows for the life sciences community. The tool includes a workbench application which provides a graphical user interface for the composition of workflows. These workflows are written in a new language called the simple conceptual unified flow language (Scufl), where by each step within a workflow represents one atomic task. Two examples are used to illustrate the ease by which in silico experiments can be represented as Scufl workflows using the workbench application.

Computational Biology↗

PubMed2004

BioRAT: extracting biological information from full-length papers.

MOTIVATION: Converting the vast quantity of free-format text found in journals into a concise, structured format makes the researcher's quest for information easier. Recently, several information extraction systems have been developed that attempt to simplify the retrieval and analysis of biological and medical data. Most of this work has used the abstract alone, owing to the convenience of access and the quality of data. Abstracts are generally available through central collections with easy direct access (e.g. PubMed). The full-text papers contain more information, but are distributed across many locations (e.g. publishers' web sites, journal web sites and local repositories), making access more difficult. In this paper, we present BioRAT, a new information extraction (IE) tool, specifically designed to perform biomedical IE, and which is able to locate and analyse both abstracts and full-length papers. BioRAT is a Biological Research Assistant for Text mining, and incorporates a document search ability with domain-specific IE. RESULTS: We show first, that BioRAT performs as well as existing systems, when applied to abstracts; and second, that significantly more information is available to BioRAT through the full-length papers than via the abstracts alone. Typically, less than half of the available information is extracted from the abstract, with the majority coming from the body of each paper. Overall, BioRAT recalled 20.31% of the target facts from the abstracts with 55.07% precision, and achieved 43.6% recall with 51.25% precision on full-length papers.

Abstracting and Indexing↗

PubMed2004

DisProt: a database of protein disorder.

UNLABELLED: The Database of Protein Disorder (DisProt) is a curated database that provides structure and function information about proteins that lack a fixed three-dimensional (3D) structure under putatively native conditions, either in their entirety or in part. Starting from the central premise that intrinsic disorder is an important structural class of protein and in order to meet the increasing interest thereof, DisProt is aimed at becoming a central repository of disorder-related information. For each disordered protein, the database includes the name of the protein, various aliases, accession codes, amino acid sequence, location of the disordered region(s), and methods used for structural (disorder) characterization. If applicable, most entries also list the biological function(s) of each disordered region, how each region of disorder is used for function, as well as provide links to PubMed abstracts and major protein databases. AVAILABILITY: www.disprot.org

Amino Acid Sequence↗

PubMed2005

YeastHub: a semantic web use case for integrating data in the life sciences domain.

MOTIVATION: As the semantic web technology is maturing and the need for life sciences data integration over the web is growing, it is important to explore how data integration needs can be addressed by the semantic web. The main problem that we face in data integration is a lack of widely-accepted standards for expressing the syntax and semantics of the data. We address this problem by exploring the use of semantic web technologies-including resource description framework (RDF), RDF site summary (RSS), relational-database-to-RDF mapping (D2RQ) and native RDF data repository-to represent, store and query both metadata and data across life sciences datasets. RESULTS: As many biological datasets are presently available in tabular format, we introduce an RDF structure into which they can be converted. Also, we develop a prototype web-based application called YeastHub that demonstrates how a life sciences data warehouse can be built using a native RDF data store (Sesame). This data warehouse allows integration of different types of yeast genome data provided by different resources in different formats including the tabular and RDF formats. Once the data are loaded into the data warehouse, RDF-based queries can be formulated to retrieve and query the data in an integrated fashion. AVAILABILITY: The YeastHub website is accessible via the following URL: http://yeasthub.gersteinlab.org.

Biology↗

PubMed2005

DPDB: a database for the storage, representation and analysis of polymorphism in the Drosophila genus.

MOTIVATION: Polymorphism studies are one of the main research areas of this genomic era. To date, however, no comprehensive secondary databases have been designed to provide searchable collections of polymorphic sequences with their associated diversity measures. RESULTS: We define a data model for the storage, representation and analysis of genotypic and haplotypic data. Under this model we have created DPDB, 'Drosophila Polymorphism Database', a web site that provides a daily updated repository of all well-annotated polymorphic sequences in the Drosophila genus. It allows the search for any polymorphic set according to different parameter values of nucleotide diversity, linkage disequilibrium and codon bias. For data collection, analysis and updating we use PDA, a pipeline that automates the process of sequence retrieval, grouping, alignment and estimation of nucleotide diversity from Genbank sequences in different functional regions. The web site also includes analysis tools for sequence comparison and the estimation of genetic diversity, a page with real-time statistics of the database contents, a help section and a collection of selected links. AVAILABILITY: DPDB is freely available at http://dpdb.uab.es and can be downloaded via FTP.

Animals↗

PubMed2005

DNA assembly with gaps (Dawg): simulating sequence evolution.

MOTIVATION: Relationships amongst taxa are inferred from biological data using phylogenetic methods and procedures. Very few known phylogenies exist against which to test the accuracy of our inferences. Therefore, in the absence of biological data, simulated data must be used to test the accuracy of methods which produce these inferences. Researchers have limited or non-existent options for simulations useful for studying the impact of insertions, deletions, and alignments on phylogenetic accuracy. RESULTS: To satisfy this gap I have developed a new algorithm of indel formation and incorporated it into a new, flexible, and portable application for sequence simulation. The application, called Dawg, simulates phylogenetic evolution of DNA sequences in continuous time using the robust general time reversible model with gamma and invariant rate heterogeneity and a novel length-dependent model of indel formation. On completion, Dawg produces the true alignment of the simulated sequences. Unlike other applications, Dawg allows indel lengths to be explicitly distributed via a biologically realistic power law. Many options are available to allow users to customize their simulations and results. Because simulating with indels would be problematic if biologically realistic parameters could not be estimated, a script is provided with Dawg that can estimate the parameters of indel formation from sequence data. Dawg was applied to the sequences of four chloroplast trnK introns. It was used to parametrically bootstrap an estimation of the rate of indel formation for the phylogeny. Because Dawg can assist in parametric bootstrapping of sequence data it is useful beyond phylogenetics, such as studying alignment algorithms or parameters of molecular evolution. AVAILABILITY: Dawg 1.0.0 can be obtained at the following websites: http://www.genetics.uga.edu/sw/ or http://scit.us/dawg/. The package includes source code, example files, a brief manual and helper scripts. Binary distributions are available for Windows and Macintosh OS X. A development page for Dawg exists at http://scit.us/dawg/, with links to a Subversion repository, mailing lists and updated versions.

Base Sequence↗

PubMed2004

The ArrayExpress gene expression database: a software engineering and implementation perspective.

MOTIVATION: The lack of microarray data management systems and databases is still one of the major problems faced by many life sciences laboratories. While developing the public repository for microarray data ArrayExpress we had to find novel solutions to many non-trivial software engineering problems. Our experience will be both relevant and useful for most bioinformaticians involved in developing information systems for a wide range of high-throughput technologies. RESULTS: ArrayExpress has been online since February 2002, growing exponentially to well over 10,000 hybridizations (as of September 2004). It has been demonstrated that our chosen design and implementation works for databases aimed at storage, access and sharing of high-throughput data. AVAILABILITY: The ArrayExpress database is available at http://www.ebi.ac.uk/arrayexpress/. The software is open source. CONTACT: ugis@ebi.ac.uk.

Algorithms↗