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At least 19 recordsLinked to original sources

PubMed2001

The Molecular Biology Database Collection: an updated compilation of biological database resources.

The Molecular Biology Database Collection is an online resource listing key databases of value to the biological community. This Collection is intended to bring fellow scientists' attention to high-quality databases that are available throughout the world, rather than just be a lengthy listing of all available databases. As such, this up-to-date listing is intended to serve as the initial point from which to find specialized databases that may be of use in biological research. The databases included in this Collection provide new value to the underlying data by virtue of curation, new data connections or other innovative approaches. Short, searchable summaries of each of the databases included in the Collection are available through the Nucleic Acids Research Web site, at http://www. nar.oupjournals.org.

Animals↗

PubMed2005

DoD: Database of Databases--updated molecular biology databases.

Database of Databases (DoD) is a collection of molecular biology databases extracted from Nucleic Acids Research, 2005 Database issue. DoD is constructed using javascript and html code. The 14 categories of 719 databases are provided with a search option, keyword help and database description linked to respective pages. Keyword help lists the search strings used to perform an individual search against categorized databases. Database description provides brief information about the database with a link to full-text article and main web page. DoD is available online and can be accessed at http://www.progenebio.in/DoD/DoD.htm.

Computational Biology↗

PubMed2005

Critical evaluation of the JDO API for the persistence and portability requirements of complex biological databases.

BACKGROUND: Complex biological database systems have become key computational tools used daily by scientists and researchers. Many of these systems must be capable of executing on multiple different hardware and software configurations and are also often made available to users via the Internet. We have used the Java Data Object (JDO) persistence technology to develop the database layer of such a system known as the SigPath information management system. SigPath is an example of a complex biological database that needs to store various types of information connected by many relationships. RESULTS: Using this system as an example, we perform a critical evaluation of current JDO technology; discuss the suitability of the JDO standard to achieve portability, scalability and performance. We show that JDO supports portability of the SigPath system from a relational database backend to an object database backend and achieves acceptable scalability. To answer the performance question, we have created the SigPath JDO application benchmark that we distribute under the Gnu General Public License. This benchmark can be used as an example of using JDO technology to create a complex biological database and makes it possible for vendors and users of the technology to evaluate the performance of other JDO implementations for similar applications. CONCLUSIONS: The SigPath JDO benchmark and our discussion of JDO technology in the context of biological databases will be useful to bioinformaticians who design new complex biological databases and aim to create systems that can be ported easily to a variety of database backends.

Computational Biology↗

PubMed1999

DATABANKS - a catalogue database of molecular biology databases.

Explore the source record for details and available documents.

Databases, Factual↗

PubMed2003

A protocol for the update of references to scientific literature in biological databases.

Entries in biological databases are usually linked to scientific references. To generate those links and to keep them up-to-date, database maintainers have to continuously scan the scientific literature to select references that are relevant for each single database entry. The continuous growth of both the corpus of scientific literature and the size of biological databases makes this task very hard. We present a protocol intended to assist the updating of an existing set of literature (abstract) links from a single database entry with new references. It consists of taking the set of MEDLINE neighbour references of the existing linked abstracts and evaluating their relevance according to the existing set of abstracts. To test the applicability of the algorithm, we did a simple benchmark of the system using the references associated with the entries of a protein domain database. Human experts found the references that the algorithm scored highly were more relevant to the database entry than those scored lowly, suggesting that the algorithm was useful.

Abstracting and Indexing↗

PubMed1998

A metadata approach to query interoperation between molecular biology databases.

MOTIVATION: Molecular biology databases have been proliferating rapidly. Their heterogeneity and complexity pose a great challenge to efforts in database interoperation. To minimize the efforts of interoperating heterogeneous databases, it is useful to develop a system that lets a user of a particular genomic database access another related database as if the latter is structurally similar to the former. RESULTS: We extend a structurally simple model-the entity-attribute-value (EAV) model-to describe uniformly metadata relating to individual databases. Such metadata, which are necessary for performing database comparisons, include descriptions of primitive database objects (including entities, attributes, domain values and entity relationships) and specification of correspondences among the database objects. We show how to decompose SQL queries and map them from one database to another based on the EAV representation of the basic database objects. A prototype system is implemented to demonstrate query interoperation between two chromosome map databases. AVAILABILITY: Freely available (Cold Fusion source code and an Access database containing the mapping knowledge) upon request from the author. CONTACT: kei.cheung@yale.edu

Chromosome Mapping↗

PubMed1999

Molecular Biology Database List.

Molecular Biology Database List (MBDL) includes brief descriptions and pointers to Web sites for the various databases described in this issue as well as other Web sites presenting data sets relevant to molecular biology. This information is compiled into a list (http://www.oup.co.uk/nar/Volume_27/Issue_01/summary/ gkc105_gml.html) which includes links both to source Web sites and to on-line versions of articles describing the databases.

Databases, Factual↗

PubMed2000

The molecular biology database collection: an online compilation of relevant database resources.

The Molecular Biology Database Collection represents an effort geared at making molecular biology database resources more accessible to biologists. This online resource, available at http://www.oup.co.uk/nar/Volume_28/Issue_01/html /gkd115_gml.html, is intended to serve as a searchable, up-to-date, centralized jumping-off point to individual Web sites. An emphasis has also been placed on including databases where new value is added to the underlying data by virtue of curation, new data connections, or other innovative approaches.

Databases, Factual↗

PubMed1995

Characterizing heterogeneous molecular biology database systems.

Molecular biology data are distributed among multiple databases. Although containing related data, these databases are often isolated and are characterized by various degrees of heterogeneity: they usually represent different views (schemas) of the scientific domain and are implemented using different data management systems. Currently, several systems support managing data in heterogeneous molecular biology databases. Lack of clear criteria for characterizing such systems precludes comprehensive evaluations of these systems or determining their relationships in terms of shared goals and facilities. In this paper, we propose criteria that would facilitate characterizing, evaluating, and comparing heterogeneous molecular biology database systems.

Computer Communication Networks↗

PubMed1998

Advanced query mechanisms for biological databases.

Existing query interfaces for biological databases are either based on fixed forms or textual query languages. Users of a fixed form-based query interface are limited to performing some pre-defined queries providing a fixed view of the underlying database, while users of a free text query language-based interface have to understand the underlying data models, specific query languages and application schemas in order to formulate queries. Further, operations on application-specific complex data (e.g., DNA sequences, proteins), which are usually provided by a variety of software packages with their own format requirements and peculiarities, are not available as part of, nor integrated with biological query interfaces. In this paper, we describe generic tools that provide powerful and flexible support for interactively exploring biological databases in a uniform and consistent way, that is via common data models, formats, and notations, in the framework of the Object-Protocol Model (OPM). These tools include (i) a Java graphical query construction tool with support for automatic generation of Web query forms that can be either used for further specifying conditions, or can be saved and customized; (ii) query processors for interpreting and executing queries that may involve complex application-specific objects, and that could span multiple heterogeneous databases and file systems; and (iii) utilities for automatic generation of HTML pages containing query results, that can be browsed using a Web browser. These tools avoid the restrictions imposed by traditional fixed-form query interfaces, while providing users with simple and intuitive facilities for formulating ad-hoc queries across heterogeneous databases, without the need to understand the underlying data models and query languages.

Animals↗

PubMed2003

SEMEDA: ontology based semantic integration of biological databases.

MOTIVATION: Many molecular biological databases are implemented on relational Database Management Systems, which provide standard interfaces like JDBC and ODBC for data and metadata exchange. By using these interfaces, many technical problems of database integration vanish and issues related to semantics remain, e.g. the use of different terms for the same things, different names for equivalent database attributes and missing links between relevant entries in different databases. RESULTS: In this publication, principles and methods that were used to implement SEMEDA (Semantic Meta Database) are described. Database owners can use SEMEDA to provide semantically integrated access to their databases as well as to collaboratively edit and maintain ontologies and controlled vocabularies. Biologists can use SEMEDA to query the integrated databases in real time without having to know the structure or any technical details of the underlying databases. AVAILABILITY: SEMEDA is available at http://www-bm.ipk-gatersleben.de/semeda/. Database providers who intend to grant access to their databases via SEMEDA are encouraged to contact the authors.

Computational Biology↗

PubMed2002

The Molecular Biology Database Collection: 2002 update.

The Molecular Biology Database Collection is an online resource listing key databases of value to the biological community. This Collection is intended to bring fellow scientists' attention to high-quality databases that are available throughout the world, rather than just be a lengthy listing of all available databases. As such, this up-to-date listing is intended to serve as the initial point from which to find specialized databases that may be of use in biological research. The databases included in this Collection provide new value to the underlying data by virtue of curation, new data connections or other innovative approaches. Short, searchable summaries and updates for each of the databases included in the Collection are available through the Nucleic Acids Research Web site at http://nar.oupjournals.org.

Computational Biology↗

PubMed2003

The Molecular Biology Database Collection: 2003 update.

The Molecular Biology Database Collection is an online resource listing key databases of value to the biological community. This Collection is intended to bring fellow scientists' attention to high-quality databases that are available throughout the world, rather than just be a lengthy listing of all available databases. As such, this up-to-date listing is intended to serve as the jumping-off point from which to find specialized databases that may be of use in advancing biological research. The databases included in this Collection provide new value to the underlying data by virtue of curation, new data connections or other innovative approaches. Short, searchable summaries and updates for each of the databases included in this Collection are available through the Nucleic Acids Research Web site at http://nar.oupjournals.org.

Data Collection↗

PubMed2006

The Molecular Biology Database Collection: 2007 update.

The NAR online Molecular Biology Database Collection is a public resource that contains links to the databases described in this issue of Nucleic Acids Research, previous NAR database issues, as well as a selection of other molecular biology databases that are freely available on the web and might be useful to the molecular biologist. The 2007 update includes 968 databases, 110 more than the previous one. Many databases that have been described in earlier issues of NAR come with updated summaries, which reflect recent progress and, in some instances, an expanded scope of these databases. The complete database list and summaries are available online on the Nucleic Acids Research web site http://nar.oxfordjournals.org/.

Databases, Genetic↗

PubMed1998

A model system for studying the integration of molecular biology databases.

MOTIVATION: Integration of molecular biology databases remains limited in practice despite its practical importance and considerable research effort. The complexity of the problem is such that an experimental approach is mandatory, yet this very complexity makes it hard to design definitive experiments. This dilemma is common in science, and one tried-and-true strategy is to work with model systems. We propose a model system for this problem, namely a database of genes integrating diverse data across organisms, and describe an experiment using this model. RESULTS: We attempted to construct a database of human and mouse genes integrating data from GenBank and the human and mouse genome-databases. We discovered numerous errors in these well-respected databases: approximately 15% of genes are apparently missing from the genome-databases; links between the sequence and genome-databases are missing for another 5-10% of the cases; about a third of likely homology links are missing between the genome-databases; 10-20% of entries classified as 'genes' are apparently misclassified. By using a model system, we were able to study the problems caused by anomalous data without having to face all the hard problems of database integration. CONTACT: nat@jax.org

Animals↗

PubMed2004

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.

Computational Biology↗

PubMed2005

The Mouse Tumor Biology Database: integrated access to mouse cancer biology data.

Mice have long been used as models for the study of human cancer. The National Cancer Institute has included among its research areas of extraordinary opportunity the development of new mouse genetic models of human cancer and the exploration of cancer imaging as a research tool. Because of the volume and interconnectedness of relevant data, the creation and maintenance of bioinformatics resources of mouse tumor biology is necessary to facilitate current and future cancer research. The Mouse Tumor Biology (MTB) Database provides electronic access to data generated through the study of spontaneous and induced tumors in genetically defined mice (inbred, hybrid, spontaneous and induced mutant, and genetically engineered strains of mice).

Animals↗

PubMed2004

The Molecular Biology Database Collection: 2004 update.

The Molecular Biology Database Collection is a public resource listing key databases of value to the biologist, including those featured in this issue of Nucleic Acids Research, and other high-quality databases. All databases included in this Collection are freely available to the public. This listing aims to serve as a convenient starting point for searching the web for reliable information on various aspects of molecular biology, biochemistry and genetics. This year's update includes 548 databases, 162 more than the previous one. The databases are organized in a hierarchical classification that should simplify finding the right database for each given task. Each database in the list comes with a recently updated brief description. The database list and the database descriptions can be accessed online at the Nucleic Acids Research web site http://nar. oupjournals.org/.

Animals↗