openBIS: a flexible framework for managing and analyzing complex data in biology research.
| Type | Information |
|---|---|
| Nr | 28 (Research article) |
| Authors | Bauch, Angela; Adamczyk, Izabela; Buczek, Piotr; Elmer, Franz-Josef; Enimanev, Kaloyan; Glyzewski, Pawel; Kohler, Manuel; Pylak, Tomasz; Quandt, Andreas; Ramakrishnan, Chandrasekhar; Beisel, Christian; Malmström, Lars; Aebersold, Ruedi; Rinn, Bernd |
| Title | openBIS: a flexible framework for managing and analyzing complex data in biology research. |
| Journal | BMC Bioinformatics (2011) 12 468 |
| DOI | 10.1186/1471-2105-12-468 |
| Citations | 155 citations (journal impact: 2.75) |
| Abstract | ABSTRACT BACKGROUND Modern data generation techniques used in distributed systems biology research projects often create datasets of enormous size and diversity. We argue that in order to overcome the challenge of managing those large quantitative datasets and maximise the biological information extracted from them a sound information system is required. Ease of integration with data analysis pipelines and other computational tools is a key requirement for it. RESULTS We have developed openBIS an open source software framework for constructing user-friendly scalable and powerful information systems for data and metadata acquired in biological experiments. openBIS enables users to collect integrate share publish data and to connect to data processing pipelines. This framework can be extended and has been customized for different data types acquired by a range of technologies. CONCLUSIONS openBIS is currently being used by several SystemsX.ch and EU projects applying mass spectrometric measurements of metabolites and proteins High Content Screening or Next Generation Sequencing technologies. The attributes that make it interesting to a large research community involved in systems biology projects include versatility simplicity in deployment flexibility to handle any biological data type and extensibility to the needs of any research domain. |
| Synopsis | This paper describes a software suit for managing large amounts of data. |