Background: Modern data generation techniques used in distributed systems biology research projects often\r\ncreate datasets of enormous size and diversity. We argue that in order to overcome the challenge of managing\r\nthose large quantitative datasets and maximise the biological information extracted from them, a sound\r\ninformation system is required. Ease of integration with data analysis pipelines and other computational tools is a\r\nkey requirement for it.\r\nResults: We have developed openBIS, an open source software framework for constructing user-friendly, scalable\r\nand powerful information systems for data and metadata acquired in biological experiments. openBIS enables users\r\nto collect, integrate, share, publish data and to connect to data processing pipelines. This framework can be\r\nextended and has been customized for different data types acquired by a range of technologies.\r\nConclusions: openBIS is currently being used by several SystemsX.ch and EU projects applying mass spectrometric\r\nmeasurements of metabolites and proteins, High Content Screening, or Next Generation Sequencing technologies.\r\nThe attributes that make it interesting to a large research community involved in systems biology projects include\r\nversatility, simplicity in deployment, scalability to very large data, flexibility to handle any biological data type and\r\nextensibility to the needs of any research domain.
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