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Modeling and managing experimental data using FuGE.
Jones, Andrew R; Lister, Allyson L; Hermida, Leandro; Wilkinson, Peter; Eisenacher, Martin; Belhajjame, Khalid; Gibson, Frank; Lord, Phil; Pocock, Matthew; Rosenfelder, Heiko; Santoyo-Lopez, Javier; Wipat, Anil; Paton, Norman W.
Affiliation
  • Jones AR; Department of Preclinical Veterinary Science, Faculty of Veterinary Science, University of Liverpool, Liverpool, United Kingdom. Andrew.Jones@liv.ac.uk
OMICS ; 13(3): 239-51, 2009 Jun.
Article in En | MEDLINE | ID: mdl-19441879
ABSTRACT
The Functional Genomics Experiment data model (FuGE) has been developed to increase the consistency and efficiency of experimental data modeling in the life sciences, and it has been adopted by a number of high-profile standardization organizations. FuGE can be used (1) directly, whereby generic modeling constructs are used to represent concepts from specific experimental activities; or (2) as a framework within which method-specific models can be developed. FuGE is both rich and flexible, providing a considerable number of modeling constructs, which can be used in a range of different ways. However, such richness and flexibility also mean that modelers and application developers have choices to make when applying FuGE in a given context. This paper captures emerging best practice in the use of FuGE in the light of the experience of several groups by (1) proposing guidelines for the use and extension of the FuGE data model; (2) presenting design patterns that reflect recurring requirements in experimental data modeling; and (3) describing a community software tool kit (STK) that supports application development using FuGE. We anticipate that these guidelines will encourage consistent usage of FuGE, and as such, will contribute to the development of convergent data standards in omics research.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Computational Biology / Genomics / Models, Theoretical Type of study: Guideline / Prognostic_studies Language: En Journal: OMICS Journal subject: BIOLOGIA MOLECULAR Year: 2009 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Computational Biology / Genomics / Models, Theoretical Type of study: Guideline / Prognostic_studies Language: En Journal: OMICS Journal subject: BIOLOGIA MOLECULAR Year: 2009 Document type: Article Affiliation country: