Querying and computing with BioCyc databases

We describe multiple methods for accessing and querying the complex and integrated cellular data in the BioCyc family of databases: access through multiple file formats, access through Application Program Interfaces (APIs) for LISP, Perl and Java, and SQL access through the BioWarehouse relational database.     

Storing biological sequence databases in relational form

SUMMARY: We have created a set of applications using Perl and Java in combination with XML technology to install biological sequence databases into an Oracle RDBMS. An easy-to-use interface using Java has been created for database query and other tools developed to integrate with our in-house bioinformatics applications. AVAILIBILITY: The database schema, DTD file, and source codes are available from the authors via email. CONTACT: guochun_ xie@merck. com     

PhenomicDB: a multi-species genotype/phenotype database for comparative phenomics

SUMMARY: We have created PhenomicDB, a multi-species genotype/phenotype database by merging public genotype/phenotype data from a wide range of model organisms and Homo sapiens. Until now these data were available in distinct organism-specific databases (e.g. WormBase, OMIM, FlyBase and MGI). We compiled this wealth of data into a single integrated resource by coarse-grained semantic mapping of the phenotypic data fields, by including common gene indices (NCBI Gene), and by the use of associated orthology relationships. With its use-case-oriented user interface, PhenomicDB allows scientists to compare and browse known phenotypes for a given gene or a set of genes from different organisms simultaneously. AVAILABILITY: PhenomicDB has been implemented at Schering AG as described below. A PhenomicDB implementation differing in some technical details has been set up for the public at Metalife AG http://www.phenomicDB.de SUPPLEMENTARY INFORMATION: database model, semantic mapping table.     

A flexible online metadata editing and management system

Our team developed a metadata editing and management system employing state of the art XML technologies initially aimed at the environmental sciences but with the potential to be useful across multiple domains. We chose a modular and distributed design for scalability, flexibility, options for customizations, and the possibility to add more functionality at a later stage. The system consists of a desktop design tool that generates code for the actual online editor, a native XML database, and an online user access management application. A Java Swing application that reads an XML schema, the design tool provides the designer with options to combine input fields into online forms with user-friendly tags and determine the flow of input forms. Based on design decisions, the tool generates XForm code for the online metadata editor which is based on the Orbeon XForms engine. The design tool fulfills two requirements: First data entry forms based on a schema are customized at design time and second the tool can generate data entry applications for any valid XML schema without relying on custom information in the schema. A configuration file in the design tool saves custom information generated at design time. Future developments will add functionality to the design tool to integrate help text, tool tips, project specific keyword lists, and thesaurus services.Cascading style sheets customize the look-and-feel of the finished editor. The editor produces XML files in compliance with the original schema, however, a user may save the input into a native XML database at any time independent of validity. The system uses the open source XML database eXist for storage and uses a MySQL relational database and a simple Java Server Faces user interface for file and access management. We chose three levels to distribute administrative responsibilities and handle the common situation of an information manager entering the bulk of the metadata but leave specifics to the actual data provider.     

PATIKAweb: a Web interface for analyzing biological pathways through advanced querying and visualization

Patikaweb provides a Web interface for retrieving and analyzing biological pathways in the Patika database, which contains data integrated from various prominent public pathway databases. It features a user-friendly interface, dynamic visualization and automated layout, advanced graph-theoretic queries for extracting biologically important phenomena, local persistence capability and exporting facilities to various pathway exchange formats.     

Semantic search among heterogeneous biological databases based on gene ontology

Various biological database systems including datacapture, data storage, data retrieval and other data pro-cessing methods have been developed. These systems havebecome effective tools for today’s genomics and relatedstudies. However, the highly distribu…     

A Chado case study: an ontology-based modular schema for representing genome-associated biological information

MOTIVATION: A few years ago, FlyBase undertook to design a new database schema to store Drosophila data. It would fully integrate genomic sequence and annotation data with bibliographic, genetic, phenotypic and molecular data from the literature representing a distillation of the first 100 years of research on this major animal model system. In developing this new integrated schema, FlyBase also made a commitment to ensure that its design was generic, extensible and available as open source, so that it could be employed as the core schema of any model organism data repository, thereby avoiding redundant software development and potentially increasing interoperability. Our question was whether we could create a relational database schema that would be successfully reused. RESULTS: Chado is a relational database schema now being used to manage biological knowledge for a wide variety of organisms, from human to pathogens, especially the classes of information that directly or indirectly can be associated with genome sequences or the primary RNA and protein products encoded by a genome. Biological databases that conform to this schema can interoperate with one another, and with application software from the Generic Model Organism Database (GMOD) toolkit. Chado is distinctive because its design is driven by ontologies. The use of ontologies (or controlled vocabularies) is ubiquitous across the schema, as they are used as a means of typing entities. The Chado schema is partitioned into integrated subschemas (modules), each encapsulating a different biological domain, and each described using representations in appropriate ontologies. To illustrate this methodology, we describe here the Chado modules used for describing genomic sequences. AVAILABILITY: GMOD is a collaboration of several model organism database groups, including FlyBase, to develop a set of open-source software for managing model organism data. The Chado schema is freely distributed under the terms of the Artistic License (http://www.opensource.org/licenses/artistic-license.php) from GMOD (www.gmod.org).     

Virus variation resources at the National Center for Biotechnology Information: dengue virus

Background  

There is an increasing number of complete and incomplete virus genome sequences available in public databases. This large body of sequence data harbors information about epidemiology, phylogeny, and virulence. Several specialized databases, such as the NCBI Influenza Virus Resource or the Los Alamos HIV database, offer sophisticated query interfaces along with integrated exploratory data analysis tools for individual virus species to facilitate extracting this information. Thus far, there has not been a comprehensive database for dengue virus, a significant public health threat.     

FlyBase--the Drosophila database. The FlyBase Consortium.

FlyBase is a database of genetic and molecular data concerning Drosophila. FlyBase is maintained as a relational database (in Sybase) and is available from the ftp.bio.indiana.edu Gopher server. The scope of FlyBase includes: genes, alleles, aberrations, pointers to sequence data, stock lists, Drosophila workers and bibliographic references.     

MetaFam: a unified classification of protein families. II. Schema and query capabilities

MOTIVATION: Protein sequence and family data is accumulating at such a rapid rate that state-of-the-art databases and interface tools are required to aid curators with their classifications. We have designed such a system, MetaFam, to facilitate the comparison and integration of public protein sequence and family data. This paper presents the global schema, integration issues, and query capabilities of MetaFam. RESULTS: MetaFam is an integrated data warehouse of information about protein families and their sequences. This data has been collected into a consistent global schema, and stored in an Oracle relational database. The warehouse implementation allows for quick removal of outdated data sets. In addition to the relational implementation of the primary schema, we have developed several derived tables that enable efficient access from data visualization and exploration tools. Through a series of straightforward SQL queries, we demonstrate the usefulness of this data warehouse for comparing protein family classifications and for functional assignment of new sequences.     

FlyBase: the Drosophila database. The Flybase Consortium.

FlyBase is a database of genetic and molecular data concerning Drosophila. FlyBase is maintained as a relational database (in Sybase). The scope of FlyBase includes: genes, alleles (and phenotypes), aberrations, pointers to sequence data, clones, stock lists, Drosophila workers and bibliographic references. FlyBase is also available on CD-ROM for Macintosh systems (Encyclopaedia of Drosophila).     

YAdumper: extracting and translating large information volumes from relational databases to structured flat files

Downloading the information stored in relational databases into XML and other flat formats is a common task in bioinformatics. This periodical dumping of information requires considerable CPU time, disk and memory resources. YAdumper has been developed as a purpose-specific tool to deal with the integral structured information download of relational databases. YAdumper is a Java application that organizes database extraction following an XML template based on an external Document Type Declaration. Compared with other non-native alternatives, YAdumper substantially reduces memory requirements and considerably improves writing performance.     

JESAM: CORBA software components to create and publish EST alignments and clusters

MOTIVATION: Expressed Sequence Tags (ESTs) are cheap, easy and quick to obtain relative to full genomic sequencing and currently sample more eukaryotic genes than any other data source. They are particularly useful for developing Sequence Tag Sites (STSs for mapping), polymorphism discovery, disease gene hunting, mass spectrometer proteomics, and most ironically for finding genes and predicting gene structure after the great effort of genomic sequencing. However, ESTs have many problems and the public EST databases contain all the errors and high redundancy intrinsic to the submitted data so it is often found that derived database views, which reduce both errors and redundancy, are more effective starting points for research than the original raw submissions. Existing derived views such as EST cluster databases and consensus databases have never published supporting evidence or intermediary results leading to difficulties trusting, correcting, and customizing the final published database. These difficulties have lead many groups to wastefully repeat the complex intermediary work of others in order to offer slightly different final views. A better approach might be to discover the most expensive common calculations used by all the approaches and then publish all intermediary results. Given a globally accessible database with a suitable component interface, like the JESAM software described in this paper, the creation of customized EST-derived databases could be achieved with minimum effort. RESULTS: Databases of EST and full-length mRNA sequences for four model organisms have been self-compared by searching for overlaps consistent with contiguity. The sequence comparisons are performed in parallel using a PVM process farm and previous results are stored to allow incremental updates with minimal effort. The overlap databases have been published with CORBA interfaces to enable flexible global access as demonstrated by example Java applet browsers. Simple cDNA supercluster databases built as alignment database clients are themselves published via CORBA interfaces browsable with prototypical applets. A comparison with UniGene Mouse and Rat databases revealed undesirable features in both and the advantages of contrasting perspectives on complex data. AVAILABILITY: The software is packaged as two Jar files available from: URL: http://corba.ebi.ac.uk/EST/jesam/jesam. html. One jar contains all the Java source code, and the other contains all the C, C++ and IDL code. Links to working examples of the alignment and cluster viewers (if remote firewall permits) can be found at http://corba.ebi.ac.uk/EST. All the Washington University mouse EST traces are available for browsing at the same URL.     

FlyBase: a Drosophila database. The FlyBase consortium.

FlyBase is a database of genetic and molecular data concerning Drosophila. FlyBase is maintained as a relational database (in Sybase) and is made available as html documents and flat files. The scope of FlyBase includes: genes, alleles (and phenotypes), aberrations, transposons, pointers to sequence data, clones, stock lists, Drosophila workers and bibliographic references. The Encyclopedia of Drosophila is a joint effort between FlyBase and the Berkeley Drosophila Genome Project which integrates FlyBase data with those from the BDGP.     

Integrated bio-entity network: a system for biological knowledge discovery

A significant part of our biological knowledge is centered on relationships between biological entities (bio-entities) such as proteins, genes, small molecules, pathways, gene ontology (GO) terms and diseases. Accumulated at an increasing speed, the information on bio-entity relationships is archived in different forms at scattered places. Most of such information is buried in scientific literature as unstructured text. Organizing heterogeneous information in a structured form not only facilitates study of biological systems using integrative approaches, but also allows discovery of new knowledge in an automatic and systematic way. In this study, we performed a large scale integration of bio-entity relationship information from both databases containing manually annotated, structured information and automatic information extraction of unstructured text in scientific literature. The relationship information we integrated in this study includes protein-protein interactions, protein/gene regulations, protein-small molecule interactions, protein-GO relationships, protein-pathway relationships, and pathway-disease relationships. The relationship information is organized in a graph data structure, named integrated bio-entity network (IBN), where the vertices are the bio-entities and edges represent their relationships. Under this framework, graph theoretic algorithms can be designed to perform various knowledge discovery tasks. We designed breadth-first search with pruning (BFSP) and most probable path (MPP) algorithms to automatically generate hypotheses--the indirect relationships with high probabilities in the network. We show that IBN can be used to generate plausible hypotheses, which not only help to better understand the complex interactions in biological systems, but also provide guidance for experimental designs.     

FlyBase: a Drosophila database. Flybase Consortium.

FlyBase (http://flybase.bio.indiana.edu/) is a comprehensive database of genetic and molecular data concerning Drosophila . FlyBase is maintained as a relational database (in Sybase) and is made available as html documents and flat files. The scope of FlyBase includes: genes, alleles (with phenotypes), aberrations, transposons, pointers to sequence data, gene products, maps, clones, stock lists, Drosophila workers and bibliographic references.     

BioNetBuilder: automatic integration of biological networks

BioNetBuilder is an open-source client-server Cytoscape plugin that offers a user-friendly interface to create biological networks integrated from several databases. Users can create networks for approximately 1500 organisms, including common model organisms and human. Currently supported databases include: DIP, BIND, Prolinks, KEGG, HPRD, The BioGrid and GO, among others. The BioNetBuilder plugin client is available as a Java Webstart, providing a platform-independent network interface to these public databases. Availability: http://err.bio.nyu.edu/cytoscape/bionetbuilder/     

HOWDY: an integrated database system for human genome research

HOWDY is an integrated database system for accessing and analyzing human genomic information (http://www-alis.tokyo.jst.go.jp/HOWDY/). HOWDY stores information about relationships between genetic objects and the data extracted from a number of databases. HOWDY consists of an Internet accessible user interface that allows thorough searching of the human genomic databases using the gene symbols and their aliases. It also permits flexible editing of the sequence data. The database can be searched using simple words and the search can be restricted to a specific cytogenetic location. Linear maps displaying markers and genes on contig sequences are available, from which an object can be chosen. Any search starting point identifies all the information matching the query. HOWDY provides a convenient search environment of human genomic data for scientists unsure which database is most appropriate for their search.     

OLS Client and OLS Dialog: Open Source Tools to Annotate Public Omics Datasets

The availability of user‐friendly software to annotate biological datasets and experimental details is becoming essential in data management practices, both in local storage systems and in public databases. The Ontology Lookup Service (OLS, http://www.ebi.ac.uk/ols ) is a popular centralized service to query, browse and navigate biomedical ontologies and controlled vocabularies. Recently, the OLS framework has been completely redeveloped (version 3.0), including enhancements in the data model, like the added support for Web Ontology Language based ontologies, among many other improvements. However, the new OLS is not backwards compatible and new software tools are needed to enable access to this widely used framework now that the previous version is no longer available. We here present the OLS Client as a free, open‐source Java library to retrieve information from the new version of the OLS. It enables rapid tool creation by providing a robust, pluggable programming interface and common data model to programmatically access the OLS. The library has already been integrated and is routinely used by several bioinformatics resources and related data annotation tools. Secondly, we also introduce an updated version of the OLS Dialog (version 2.0), a Java graphical user interface that can be easily plugged into Java desktop applications to access the OLS. The software and related documentation are freely available at https://github.com/PRIDE-Utilities/ols-client and https://github.com/PRIDE-Toolsuite/ols-dialog .