Integrative bioinformatics
Integrative bioinformatics is a discipline of bioinformatics that focuses on problems of data integration for the life sciences.
With the rise of high-throughput (HTP) technologies in the life sciences, particularly in molecular biology, the amount of collected data has grown in an exponential fashion. Furthermore, the data is scattered over a plethora of both public and private repositories, and is stored using a large number of different formats. This situation makes the extraction of new knowledge from the complete set of available data very difficult.
Integrative bioinformatics attempts to tackle this problem by providing unified access to life science data.
Approaches
Semantic web approaches
Data warehousing approaches
In the data warehousing strategy, the data from different sources are extracted and integrated in a single database. For example, various ‘omics’ datasets may be integrated to provide biological insights into biological systems. Examples include data from genomics, transcriptomics, proteomics, interactomics, metabolomics. Ideally, changes in these sources are regularly synchronized to the integrated database. The data is presented to the users in a common format. One advantage of this approach is that data is available for analysis at a single site, using a uniform schema. Some disadvantages are that the datasets are often huge and are difficult to keep up to date.
Other approaches
See also
References
External links
 | This article has not been added to any content categories. Please help out by adding categories to it so that it can be listed with similar articles, in addition to a stub category. (August 2010) |
  | This bioinformatics-related article is a stub. You can help Wikipedia by expanding it. |