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      BioMart: driving a paradigm change in biological data management

      editorial
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      Database: The Journal of Biological Databases and Curation
      Oxford University Press

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          Abstract

          Biological data management is a challenging undertaking. It is challenging for database designers, because biological concepts are complex and not always well defined, and therefore the data models that are used to represent them are constantly changing as new techniques are developed and new information becomes available. It is challenging for collaborating groups based in different geographical locations who wish to have unified access to their distributed data sources, because combining and presenting their data creates logistical difficulties. Finally, it is challenging for users of biological databases, because in order to correctly interpret the experimental data located in one database, additional information from other databases is frequently needed, requiring the user to learn multiple systems. The BioMart project (www.biomart.org) was initiated to address these challenges. The BioMart software is based on two fundamental concepts: data agnostic modelling and data federation. Data agnostic modelling simplifies the difficult and time-consuming task of data modelling. In BioMart, this is achieved by using a predefined, query-optimized relational schema that can be used to represent any kind of data (1). Data federation makes it possible to organize multiple, disparate and distributed database systems into what appears to be a single integrated virtual database. It therefore allows users to access and cross reference data from these data sources using a single user interface, without the need for database administrators to physically collate the data in one location. Using these fundamental concepts, the BioMart project has driven a change in the biological data management paradigm, where individual biological databases are managed by different custom built systems. To give more control to both the users and the data providers, a new, innovative solution was required. BioMart started by adapting data warehousing ideas to create one universal software system for biological data management and empower biologists with the ability to create complex, customized datasets through a web interface without the need for bioinformatics support (1). It subsequently introduced a new innovative way of creating large multi-database repositories that avoid the need to store all the data in a single location (2), and finally it proved that large-scale projects involving next generation sequencing data can be managed efficiently in a distributed environment (3). BioMart has successfully adapted data warehousing ideas such as data marts, dimensional modelling (4), and query optimization into the world of biological databases (5–13). BioMart's ability to quickly deploy a website hosting any type of data, user-friendly graphical user interface, several programmatic interfaces and support for third party tools contributed to its success and adoption by many different types of projects around the world as their data management platform (14). During the 10 years of its existence, BioMart has grown from humble beginnings as a ‘data mining extension’ for the Ensembl website (1), to become an international collaboration involving large number of different organizations located on five continents: Asia, Australia, Europe, North America and South America (3,15). It has a large community of users and developers and it has been successfully used in both academia and industry. The latest version of the BioMart software has been significantly enhanced with numerous graphical user interfaces that are tailored to different user groups. In addition, it has been further improved by parallel query processing, it is now extensible with different analysis tools and the installation process can be effortlessly completed with just a few mouse clicks (16). Building on the wealth of information that has become accessible through the BioMart interface, the BioMart Central Portal (15) has introduced an innovative alternative to the large data stores maintained by specialized organizations such as The European Bioinformatics Institute (EBI) or The National Center for Biotechnology Information (NCBI). BioMart Central Portal is a first-of-its-kind, community-driven effort to provide unified access to dozens of biological databases. All development and maintenance of individual databases is left to the individual data providers, making it a very cost-effective approach. The groups that maintain individual sources can do so at their own location without the necessity of any data exchange procedures. In addition, they can draw on the wealth of information available through the portal to expose their data in the context of third party annotations. The BioMart Central Portal approach is very democratic: everyone can join or remove their data source at any time. BioMart Central Portal is effectively a ‘Virtual Bioinformatics Institute’ with no onsite personnel, minimal administration, and a very ‘green’ footprint. More recently, the International Cancer Genome Consortium (ICGC) Data Portal has demonstrated how BioMart can scale to manage large collaborative projects involving next generation sequencing data (3). The ICGC is generating data on an unprecedented scale by sequencing 500 cancer genomes and matched normal control genomes for 50 different cancer types (17). The effort is distributed between multiple participating countries and sequencing centres. Given the scale of the effort, moving all of the data to a single location is impractical. Instead, the ICGC Data Portal relies on BioMart data federation. By replicating and distributing the data model across different centres that produce the same type of data according to the same recipe, the scalability of the effort is greatly improved. Each centre is only responsible for managing their own data while data access to all of the consortium data is managed by the BioMart software. This presents a scalable approach, not only in the traditional sense of parallelizing data processing and storage, but also in a more general sense of outsourcing the external annotation expertise by federating annotations from additional, independently-maintained databases that are available in the BioMart Central Portal. The future developments for BioMart involve specialized ‘pre-packaged’ and reusable data portals. One example already in development is the OncoPortal, aimed at researchers managing cancer data. It will include preconfigured access to sources of annotations that are useful for cancer research such as Ensembl (5), Reactome (12), COSMIC (9), Pancreatic Expression Database (10) and others. It will also include a set of tools that are specifically designed for cancer data analysis. There are plans to build other preconfigured portals for different research areas, such as a mouse portal and a model organism portal. It is an ambition of the BioMart community that the BioMart project remains at the forefront of innovative solutions for biological data management in the years to come. By creating these specialized solutions and further reducing the barriers to entry, the aim is to encourage more groups to share their data through BioMart, thereby further enhancing the entire BioMart community.

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          Most cited references20

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          EnsMart: a generic system for fast and flexible access to biological data.

          The EnsMart system (www.ensembl.org/EnsMart) provides a generic data warehousing solution for fast and flexible querying of large biological data sets and integration with third-party data and tools. The system consists of a query-optimized database and interactive, user-friendly interfaces. EnsMart has been applied to Ensembl, where it extends its genomic browser capabilities, facilitating rapid retrieval of customized data sets. A wide variety of complex queries, on various types of annotations, for numerous species are supported. These can be applied to many research problems, ranging from SNP selection for candidate gene screening, through cross-species evolutionary comparisons, to microarray annotation. Users can group and refine biological data according to many criteria, including cross-species analyses, disease links, sequence variations, and expression patterns. Both tabulated list data and biological sequence output can be generated dynamically, in HTML, text, Microsoft Excel, and compressed formats. A wide range of sequence types, such as cDNA, peptides, coding regions, UTRs, and exons, with additional upstream and downstream regions, can be retrieved. The EnsMart database can be accessed via a public Web site, or through a Java application suite. Both implementations and the database are freely available for local installation, and can be extended or adapted to 'non-Ensembl' data sets.
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            BioMart Central Portal—unified access to biological data

            BioMart Central Portal (www.biomart.org) offers a one-stop shop solution to access a wide array of biological databases. These include major biomolecular sequence, pathway and annotation databases such as Ensembl, Uniprot, Reactome, HGNC, Wormbase and PRIDE; for a complete list, visit, http://www.biomart.org/biomart/martview. Moreover, the web server features seamless data federation making cross querying of these data sources in a user friendly and unified way. The web server not only provides access through a web interface (MartView), it also supports programmatic access through a Perl API as well as RESTful and SOAP oriented web services. The website is free and open to all users and there is no login requirement.
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              BioMart: a data federation framework for large collaborative projects

              BioMart is a freely available, open source, federated database system that provides a unified access to disparate, geographically distributed data sources. It is designed to be data agnostic and platform independent, such that existing databases can easily be incorporated into the BioMart framework. BioMart allows databases hosted on different servers to be presented seamlessly to users, facilitating collaborative projects between different research groups. BioMart contains several levels of query optimization to efficiently manage large data sets and offers a diverse selection of graphical user interfaces and application programming interfaces to ensure that queries can be performed in whatever manner is most convenient for the user. The software has now been adopted by a large number of different biological databases spanning a wide range of data types and providing a rich source of annotation available to bioinformaticians and biologists alike. Database URL: http://www.biomart.org
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                Author and article information

                Journal
                Database (Oxford)
                database
                databa
                Database: The Journal of Biological Databases and Curation
                Oxford University Press
                1758-0463
                2011
                12 November 2011
                12 November 2011
                : 2011
                : bar049
                Affiliations
                Ontario Institute for Cancer Research, MaRS Centre, South Tower, 101 College Street, Suite 800 Toronto, Ontario, M5G 0A3, Canada.
                Author notes
                * Corresponding author: Tel: 647 258 4321; Fax: 647-258-4321; Email: arek.kasprzyk@ 123456gmail.com
                Article
                bar049
                10.1093/database/bar049
                3215098
                22083790
                a941efde-e6bd-4020-b6fb-c907ed2edc1b
                © The Author(s) 2011. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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                Page count
                Pages: 3
                Categories
                Editorial

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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