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Integration of Large-Scale Data in Bioinformatics Bears Fundamental Significance for Biological Studies
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Data integration plays an important role in biological studies brought by the rapid development of sequencing technologies and consequently fast growing volume of biological data, researchers say.

Professor YU Jun and Prof. ZHANG Zhang from Beijing Institute of Genomics(BIG), Chinese Academy of Sciences(CAS) recently participated in the completion of a book titled “Bioinformatics-Trends and Methodologies”, and accomplished one of its chapters, introduced data integration of large-scale date in bioinformatics.

Currently, data sources in bioinformatics are geographically distributed and heterogeneous in terms of their functions, structures, data access methods and dissemination formats. This situation causes time-consuming on data processing and requires high skillfulness for researchers to solve bioinformatical tasks. Therefore, data integration has the potential to facilitate a better and more comprehensive scope of inference for biological studies.

Efforts have been devoted into biological data integration over the past two decades. Main approaches are roughly classified into five groups: data warehousing, federated databasing, service-oriented integration, semantic integration and wiki-based integration. However, barely any of them has achieved a pre-eminent impact on their field yet. With the fast growing of NGS data, the need for data integration is persistently demanding and challenges are greatly increasing.

Researchers in bioinformatics field will be continuously putting efforts on integration of large-scale data, which not only requires adoption of informatics advances but also needs communications and collaborations among people in related biological areas to form a scientific social community.

The chapter can be downloaded at http://www.intechopen.com/articles/show/title/data-integration-in-bioinformatics-current-efforts-and-challenges

Contact:  Professor YU Jun  Email: junyu@big.ac.cn

     Professor ZHANG Zhang  Email: zhangzhang@big.ac.cn