The semantic metadatabase (SEMEDA): ontology based integration of federated molecular biological data sources

A system for "intelligent" semantic integration and querying of federated databases is being implemented by using three main components: A component which enables SQL access to integrated databases by database federation (MARGBench), an ontology based semantic metadatabase (SEMEDA) and an ontology based query interface (SEMEDA-query). In this publication we explain and demonstrate the principles, architecture and the use of SEMEDA. Since SEMEDA is implemented as 3 tiered web application database providers can enter all relevant semantic and technical information about their databases by themselves via a web browser. SEMEDA' s collaborative ontology editing feature is not restricted to database integration, and might also be useful for ongoing ontology developments, such as the "Gene Ontology" [2]. SEMEDA can be found at http://www-bm.cs.uni-magdeburg.de/semeda/. We explain how this ontologically structured information can be used for semantic database integration. In addition, requirements to ontologies for molecular biological database integration are discussed and relevant existing ontologies are evaluated. We further discuss how ontologies and structured knowledge sources can be used in SEMEDA and whether they can be merged supplemented or updated to meet the requirements for semantic database integration.     

The EMBL Nucleotide Sequence Database: major new developments

The EMBL Nucleotide Sequence Database (http://www.ebi.ac.uk/embl/) incorporates, organizes and distributes nucleotide sequences from all available public sources. The database is located and maintained at the European Bioinformatics Institute (EBI) near Cambridge, UK. In an international collaboration with DDBJ (Japan) and GenBank (USA), data are exchanged amongst the collaborating databases on a daily basis to achieve optimal synchronization. Webin is the preferred web-based submission system for individual submitters, while automatic procedures allow incorporation of sequence data from large-scale genome sequencing centres and from the European Patent Office (EPO). Database releases are produced quarterly. Network services allow free access to the most up-to-date data collection via FTP, Email and World Wide Web interfaces. EBI's Sequence Retrieval System (SRS) integrates and links the main nucleotide and protein databases plus many other specialized molecular biology databases. For sequence similarity searching, a variety of tools (e.g. Fasta, BLAST) are available which allow external users to compare their own sequences against the latest data in the EMBL Nucleotide Sequence Database and SWISS-PROT. All resources can be accessed via the EBI home page at http://www.ebi.ac.uk.     

The EMBL nucleotide sequence database

The EMBL Nucleotide Sequence Database (http://www.ebi.ac.uk/embl/) is maintained at the European Bioinformatics Institute (EBI) in an international collaboration with the DNA Data Bank of Japan (DDBJ) and GenBank at the NCBI (USA). Data is exchanged amongst the collaborating databases on a daily basis. The major contributors to the EMBL database are individual authors and genome project groups. Webin is the preferred web-based submission system for individual submitters, whilst automatic procedures allow incorporation of sequence data from large-scale genome sequencing centres and from the European Patent Office (EPO). Database releases are produced quarterly. Network services allow free access to the most up-to-date data collection via ftp, email and World Wide Web interfaces. EBI's Sequence Retrieval System (SRS), a network browser for databanks in molecular biology, integrates and links the main nucleotide and protein databases plus many specialized databases. For sequence similarity searching a variety of tools (e.g. Blitz, Fasta, BLAST) are available which allow external users to compare their own sequences against the latest data in the EMBL Nucleotide Sequence Database and SWISS-PROT.     

A database of unique protein sequence identifiers for proteome studies

In proteome studies, identification of proteins requires searching protein sequence databases. The public protein sequence databases (e.g., NCBInr, UniProt) each contain millions of entries, and private databases add thousands more. Although much of the sequence information in these databases is redundant, each database uses distinct identifiers for the identical protein sequence and often contains unique annotation information. Users of one database obtain a database-specific sequence identifier that is often difficult to reconcile with the identifiers from a different database. When multiple databases are used for searches or the databases being searched are updated frequently, interpreting the protein identifications and associated annotations can be problematic. We have developed a database of unique protein sequence identifiers called Sequence Globally Unique Identifiers (SEGUID) derived from primary protein sequences. These identifiers serve as a common link between multiple sequence databases and are resilient to annotation changes in either public or private databases throughout the lifetime of a given protein sequence. The SEGUID Database can be downloaded (http://bioinformatics.anl.gov/SEGUID/) or easily generated at any site with access to primary protein sequence databases. Since SEGUIDs are stable, predictions based on the primary sequence information (e.g., pI, Mr) can be calculated just once; we have generated approximately 500 different calculations for more than 2.5 million sequences. SEGUIDs are used to integrate MS and 2-DE data with bioinformatics information and provide the opportunity to search multiple protein sequence databases, thereby providing a higher probability of finding the most valid protein identifications.     

Wrapping and interoperating bioinformatics resources using CORBA

Bioinformaticians seeking to provide services to working biologists are faced with the twin problems of distribution and diversity of resources. Bioinformatics databases are distributed around the world and exist in many kinds of storage forms, platforms and access paradigms. To provide adequate services to biologists, these distributed and diverse resources have to interoperate seamlessly within single applications. The Common Object Request Broker Architecture (CORBA) offers one technical solution to these problems. The key component of CORBA is its use of object orientation as an intermediate form to translate between different representations. This paper concentrates on an explanation of object orientation and how it can be used to overcome the problems of distribution and diversity by describing the interfaces between objects.     

The EMBL Nucleotide Sequence Database

The EMBL Nucleotide Sequence Database (aka EMBL-Bank; http://www.ebi.ac.uk/embl/) incorporates, organises and distributes nucleotide sequences from all available public sources. EMBL-Bank is located and maintained at the European Bioinformatics Institute (EBI) near Cambridge, UK. In an international collaboration with DDBJ (Japan) and GenBank (USA), data are exchanged amongst the collaborating databases on a daily basis. Major contributors to the EMBL database are individual scientists and genome project groups. Webin is the preferred web-based submission system for individual submitters, whilst automatic procedures allow incorporation of sequence data from large-scale genome sequencing centres and from the European Patent Office (EPO). Database releases are produced quarterly. Network services allow free access to the most up-to-date data collection via FTP, email and World Wide Web interfaces. EBI’s Sequence Retrieval System (SRS), a network browser for databanks in molecular biology, integrates and links the main nucleotide and protein databases plus many other specialized databases. For sequence similarity searching, a variety of tools (e.g. Blitz, Fasta, BLAST) are available which allow external users to compare their own sequences against the latest data in the EMBL Nucleotide Sequence Database and SWISS-PROT. All resources can be accessed via the EBI home page at http://www.ebi.ac.uk.     

Light-weight integration of molecular biological databases

MOTIVATION: Due to the increasing number of molecular biological databases and the exponential growth of their contents, database integration is an important topic of research in bioinformatics. Existing approaches in this area have in common that considerable efforts are needed to provide integrated access to heterogeneous data sources. RESULTS: This article describes the LIMBO architecture as a light-weight approach to molecular biological database integration. By building systems upon this architecture, the efforts needed for database integration can be significantly lowered. AVAILABILITY: As an illustration of the principle usefulness of the underlying ideas, a prototypical implementation based upon the LIMBO architecture is described. This implementation is exclusively based on freely available open source components like the PostgreSQL database management system and the BioRuby project. Additional files and modified components are available upon request from the author.     

The EMBL nucleotide sequence database

The European Molecular Biology Laboratory (EMBL) Nucleotide Sequence Database (http://www.ebi.ac. uk/embl/index.html ) is maintained at the European Bioinformatics Institute (EBI) in an international collaboration with the DNA Data Bank of Japan (DDBJ) and GenBank (USA). Data is exchanged amongst the collaborative databases on a daily basis. The major contributors to the EMBL database are individual authors and genome project groups. WEBIN is the preferred web-based submission system for individual submitters, whilst automatic procedures allow incorporation of sequence data from large-scale genome sequencing centres and from the European Patent Office (EPO). Database releases are produced quarterly. Network services allow free access to the most up-to-date data collection via Internet and WWW interfaces. EBI's Sequence Retrieval System (SRS) is a network browser for databanks in molecular biology, integrating and linking the main nucleotide and protein databases plus many specialised databases. For sequence similarity searching a variety of tools (e.g., BLITZ, FASTA, BLAST) are available which allow external users to compare their own sequences against the most currently available data in the EMBL Nucleotide Sequence Database and SWISS-PROT.     

The Princeton Protein Orthology Database (P-POD): a comparative genomics analysis tool for biologists

Many biological databases that provide comparative genomics information and tools are now available on the internet. While certainly quite useful, to our knowledge none of the existing databases combine results from multiple comparative genomics methods with manually curated information from the literature. Here we describe the Princeton Protein Orthology Database (P-POD, http://ortholog.princeton.edu), a user-friendly database system that allows users to find and visualize the phylogenetic relationships among predicted orthologs (based on the OrthoMCL method) to a query gene from any of eight eukaryotic organisms, and to see the orthologs in a wider evolutionary context (based on the Jaccard clustering method). In addition to the phylogenetic information, the database contains experimental results manually collected from the literature that can be compared to the computational analyses, as well as links to relevant human disease and gene information via the OMIM, model organism, and sequence databases. Our aim is for the P-POD resource to be extremely useful to typical experimental biologists wanting to learn more about the evolutionary context of their favorite genes. P-POD is based on the commonly used Generic Model Organism Database (GMOD) schema and can be downloaded in its entirety for installation on one's own system. Thus, bioinformaticians and software developers may also find P-POD useful because they can use the P-POD database infrastructure when developing their own comparative genomics resources and database tools.     

A web-based GIS tool for exploring the world's biodiversity: The Global Biodiversity Information Facility Mapping and Analysis Portal Application (GBIF-MAPA)

Legacy biodiversity data from natural history and survey collections are rapidly becoming available in a common format over the Internet. Over 110 million records are already being served from the Global Biodiversity Information Facility (GBIF). However, our ability to use this information effectively for ecological research, management and conservation lags behind. A solution is a web-based Geographic Information System for enabling visualization and analysis of this rapidly expanding data resource. In this paper we detail a case study system, GBIF Mapping and Analysis Portal Application (MAPA), developed for deployment at distributed database portals. Building such a system requires overcoming a series of technical and research challenges. These challenges include: assuring fast speed of access to the vast amounts of data available through these distributed biodiversity databases; developing open standards based access to suitable environmental data layers for analyzing biodiversity distribution; building suitably flexible and intuitive map interfaces for refining the scope and criteria of an analysis; and building appropriate web-services based analysis tools that are of primary importance to the ecological community and make manifest the value of online biodiversity GBIF data. After discussing how we overcome these challenges, we provide case studies showing two examples of the use of GBIF-MAPA analysis tools.     

Biomolecular interaction network database

This software review looks at the utility of the Biomolecular Interaction Network Database (BIND) as a web database. BIND offers methods common to related biology databases and specialisations for its protein interaction data. Searching and browsing this database is easy and well integrated with the underlying data and the needs of scientists. Interaction networks are visualised with software that offers many useful options. The innovative ontoglyphs are used throughout to provide visual cues to protein functions, localisation and other aspects one needs to know for this data set. One can expect to get useful results that may be well integrated with one's research needs.     

Protein Information Resource: a community resource for expert annotation of protein data

The Protein Information Resource, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), produces the most comprehensive and expertly annotated protein sequence database in the public domain, the PIR-International Protein Sequence Database. To provide timely and high quality annotation and promote database interoperability, the PIR-International employs rule-based and classification-driven procedures based on controlled vocabulary and standard nomenclature and includes status tags to distinguish experimentally determined from predicted protein features. The database contains about 200,000 non-redundant protein sequences, which are classified into families and superfamilies and their domains and motifs identified. Entries are extensively cross-referenced to other sequence, classification, genome, structure and activity databases. The PIR web site features search engines that use sequence similarity and database annotation to facilitate the analysis and functional identification of proteins. The PIR-Inter-national databases and search tools are accessible on the PIR web site at http://pir.georgetown.edu/ and at the MIPS web site at http://www.mips.biochem.mpg.de. The PIR-International Protein Sequence Database and other files are also available by FTP.     

Towards Interoperability in Genome Databases: The MAtDB (MIPS Arabidopsis Thaliana Database) Experience

Increasing numbers of whole-genome sequences are available, but to interpret them fully requires more than listing all genes. Genome databases are faced with the challenges of integrating heterogenous data and enabling data mining. In comparison to a data warehousing approach, where integration is achieved through replication of all relevant data in a unified schema, distributed approaches provide greater flexibility and maintainability. These are important in a field where new data is generated rapidly and our understanding of the data changes. Interoperability between distributed data sources allows data maintenance to be separated from integration and analysis. Simple ways to access the data can facilitate the development of new data mining tools and the transition from model genome analysis to comparative genomics. With the MIPS Arabidopsis thaliana genome database (MAtDB, http://mips.gsf.de/proj/thal/db) our aim is to go beyond a data repository towards creating an integrated knowledge resource. To this end, the Arabidopsis genome has been a backbone against which to structure and integrate heterogenous data. The challenges to be met are continuous updating of data, the design of flexible data models that can evolve with new data, the integration of heterogenous data, e.g. through the use of ontologies, comprehensive views and visualization of complex information, simple interfaces for application access locally or via the Internet, and knowledge transfer across species.     

Design and realization of an on-line database for multidimensional microscopic images of biological specimens

The BioImage database is a new scientific database for multidimensional microscopic images of biological specimens, which is available through the World Wide Web (WWW). The development of this database has followed an iterative approach, in which requirements and functionality have been revised and extended. The complexity and innovative use of the data meant that technical and biological expertise has been crucial in the initial design of the data model. A controlled vocabulary was introduced to ensure data consistency. Pointers are used to reference information stored in other databases. The data model was built using InfoModeler as a database design tool. The database management system is the Informix Dynamic Server with Universal Data Option. This object-relational system allows the handling of complex data using features such as collection types, inheritance, and user-defined data types. Informix datablades are used to provide additional functionality: the Web Integration Option enables WWW access to the database; the Video Foundation Blade provides functionality for video handling.     

READ: RIKEN Expression Array Database

READ, the RIKEN Expression Array Database, is a database of expression profile data from the RIKEN mouse cDNA microarray. It stores the microarray experimental data and information, and provides Web interfaces for researchers to use to retrieve, analyze and display their data. The goals for READ are to serve as a storage site for microarray data from ongoing research in the RIKEN mouse encyclopedia project and to provide useful links and tools to decipher biologically important information. The gene information is based mainly on the fully annotated FANTOM database. READ can be accessed at http://read.gsc.riken.go.jp/. READ also provides a search tool [READ integrates gene expression neighbor (RINGENE)] for genes with similarities in expression profiling.