openBIS: a flexible framework for managing and analyzing complex data in biology research

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• 作者：Angela Bauch (1)
  Izabela Adamczyk (1)
  Piotr Buczek (1)
  Franz-Josef Elmer (1) (2)
  Kaloyan Enimanev (1) (2)
  Pawel Glyzewski (1) (2)
  Manuel Kohler (1) (2)
  Tomasz Pylak (1) (2)
  Andreas Quandt (4)
  Chandrasekhar Ramakrishnan (1) (2)
  Christian Beisel (3)
  Lars Malmstr?m (4)
  Ruedi Aebersold (4) (5)
  Bernd Rinn (1) (2)
  
• 刊名：BMC Bioinformatics
• 出版年：2011
• 出版时间：December 2011
• 年：2011
• 卷：12
• 期：1
• 全文大小：968KB
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• 作者单位：Angela Bauch (1)
  Izabela Adamczyk (1)
  Piotr Buczek (1)
  Franz-Josef Elmer (1) (2)
  Kaloyan Enimanev (1) (2)
  Pawel Glyzewski (1) (2)
  Manuel Kohler (1) (2)
  Tomasz Pylak (1) (2)
  Andreas Quandt (4)
  Chandrasekhar Ramakrishnan (1) (2)
  Christian Beisel (3)
  Lars Malmstr?m (4)
  Ruedi Aebersold (4) (5)
  Bernd Rinn (1) (2)
  
  1. Department of Biosystems Science and Engineering, Center for Information Sciences and Databases, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland
  2. Swiss Institute of Bioinformatics (SIB), Kragujevac, Switzerland
  4. Department of Biology, Institute of Molecular Systems Biology, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland
  3. Department of Biosystems Science and Engineering, Quantitative Genomics Facility, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland
  5. Faculty of Science, University of Zurich, Kragujevac, Switzerland
  
• ISSN：1471-2105

文摘

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, scalability to very large data, flexibility to handle any biological data type and extensibility to the needs of any research domain.