2009/08/04 by Gerhard Mayer, Mayer, Gerhard · 1 voice
Biochemistry, Genetics and Molecular Biology · Computer Science · Decision Sciences · #Biomedical Text Mining and Ontologies #Data Structures and Algorithms (cs.DS) #Databases (cs.DB) #FOS: Biological sciences #FOS: Computer and information sciences #Genetics, Bioinformatics, and Biomedical Research #J.3 #Other Quantitative Biology (q-bio.OT) #Scientific Computing and Data Management #cs.DB #cs.DS #q-bio.OT
paper · pdf · doi:10.48550/arxiv.0908.0411
20 pages
openalex publication_date 2009/08/04 · arxiv published 2009/08/04 · arxiv created 2009/12/15 · arxiv updated 2009/12/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Large systems biology projects can encompass several workgroups often located in different countries. An overview about existing data standards in systems biology and the management, storage, exchange and integration of the generated data in large distributed research projects is given, the pros and cons of the different approaches are illustrated from a practical point of view, the existing software - open source as well as commercial - and the relevant literature is extensively overview, so that the reader should be enabled to decide which data management approach is the best suited for his special needs. An emphasis is laid on the use of workflow systems and of TAB-based formats. The data in this format can be viewed and edited easily using spreadsheet programs which are familiar to the working experimental biologists. The use of workflows for the standardized access to data in either own or publicly available databanks and the standardization of operation procedures is presented. The use of ontologies and semantic web technologies for data management will be discussed in a further paper.